{
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  "packName": "Education Theory & Learning Technology",
  "packVersion": "1.0.3",
  "icon": "🎓",
  "shortName": "EdTech",
  "description": "From Pavlov to Khanmigo: a complete tour of how humans learn — the foundational learning theories (behaviorism, cognitivism, constructivism), Bloom's taxonomy and the 2 Sigma Problem, the cognitive science of memory and flow, instructional-design frameworks, Sal Khan's AI vision, the modern EdTech landscape, and the field's essential vocabulary.",
  "author": "Flash Feed",
  "language": "en",
  "tagsVocabulary": [
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    "action-verbs",
    "addie",
    "affective-domain",
    "ai",
    "ai-adaptive",
    "ai-tutors",
    "assessment-data",
    "behaviorism",
    "blooms-taxonomy",
    "brave-new-words",
    "by-the-numbers",
    "cognitive-levels",
    "cognitive-load",
    "cognitivism",
    "connectivism",
    "constructivism",
    "criticism",
    "critique",
    "digital-age",
    "dual-coding",
    "ebbinghaus",
    "edtech",
    "effect-sizes",
    "equity",
    "ethics",
    "evidence",
    "flow",
    "forgetting-curve",
    "framework",
    "frameworks",
    "gagne",
    "gamification",
    "hebbian",
    "history",
    "implications",
    "instructional-design",
    "investment",
    "key-concept",
    "keyword-method",
    "khanmigo",
    "language-learning",
    "learning-science",
    "lesson-design",
    "lms",
    "market",
    "mastery-learning",
    "mechanics",
    "memory",
    "method-of-loci",
    "mnemonics",
    "modes",
    "motivation",
    "myth",
    "neuroscience",
    "original-revised",
    "pedagogy",
    "person",
    "personalization",
    "platforms",
    "references",
    "research",
    "research-assistants",
    "retrieval",
    "sci-fi",
    "socratic",
    "spaced-repetition",
    "stages",
    "standards",
    "taxonomy",
    "teacher-tools",
    "testing-effect",
    "theorist",
    "theorists",
    "theory",
    "thing",
    "thinkers",
    "two-sigma",
    "udl",
    "vocabulary"
  ],
  "items": [
    {
      "id": "lt-fact-hebbian",
      "shape": "fact",
      "title": "Neurons that fire together, wire together",
      "body": "Learning is biological. At the cellular level, acquiring knowledge means forming and strengthening **synaptic connections** between neurons — the principle summarized as *\"neurons that fire together, wire together,\"* known as **Hebbian learning**.",
      "tags": [
        "learning-science",
        "neuroscience",
        "hebbian"
      ],
      "studyGuideAnchor": "neurons-that-fire-together-wire-together",
      "illustration": {
        "imageSearchTerm": "Neurons that fire together wire together",
        "imagePrompt": "Neurons that fire together, wire together. Learning is biological. At the cellular level, acquiring knowledge means forming and strengthening **synaptic connections** between neurons — the principle summarized as *\"neurons",
        "alt": "Neurons that fire together, wire together",
        "credit": "Pexels · Google DeepMind",
        "creditUrl": "https://www.pexels.com/photo/an-artist-s-illustration-of-artificial-intelligence-ai-this-image-represents-how-machine-learning-is-inspired-by-neuroscience-and-the-human-brain-it-was-created-by-novoto-studio-as-par-17483867/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-hebbian.webp"
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    {
      "id": "lt-def-hebbian",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Hebbian learning"
      },
      "definition": {
        "modality": "text",
        "value": "The principle that synaptic connections between neurons strengthen when they activate together — 'neurons that fire together, wire together.'"
      },
      "tags": [
        "learning-science",
        "neuroscience"
      ],
      "uid": "1vcwspbf2q6n1"
    },
    {
      "id": "lt-fact-three-stages",
      "shape": "fact",
      "title": "Exposure, retrieval, application",
      "body": "Effective learning requires three stages of engagement: **exposure** to new information, **retrieval** of that information from memory, and **application** in progressively complex contexts. It isn't linear — strong learning cycles through these repeatedly.",
      "tags": [
        "learning-science",
        "neuroscience",
        "stages"
      ],
      "factVariant": "image-heavy",
      "imageCaption": "Learn in three moves: exposure, retrieval, application.",
      "illustration": {
        "imagePrompt": "Evocative photograph for a hero card: Hands writing notes beside a stack of books",
        "imageSearchTerm": "studying notes books",
        "alt": "Hands writing notes beside a stack of books",
        "credit": "Pexels · Mikhail Nilov",
        "creditUrl": "https://www.pexels.com/photo/a-person-writing-on-a-notebook-7054499/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-three-stages.webp"
      },
      "studyGuideAnchor": "exposure-retrieval-application",
      "uid": "bz7fir1gevech"
    },
    {
      "id": "lt-pair-passive",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Passive learning"
      },
      "sideB": {
        "modality": "text",
        "value": "Observing, watching, reading — weak for retention"
      },
      "tags": [
        "learning-science",
        "modes"
      ],
      "uid": "1vvjwtrasgtrh"
    },
    {
      "id": "lt-pair-active",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Active learning"
      },
      "sideB": {
        "modality": "text",
        "value": "Recalling, practicing, testing — reinforces neural pathways"
      },
      "tags": [
        "learning-science",
        "modes"
      ],
      "uid": "19yo7ay1xuahz2"
    },
    {
      "id": "lt-pair-interactive",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Interactive learning"
      },
      "sideB": {
        "modality": "text",
        "value": "Teaching, debating, contributing — the deepest retrieval"
      },
      "tags": [
        "learning-science",
        "modes"
      ],
      "uid": "yhod9l140wl9v"
    },
    {
      "id": "lt-mcq-deepest-mode",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "Which pair of activities defines the interactive mode of learning?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Recalling and practicing"
        },
        {
          "modality": "text",
          "value": "Teaching and debating"
        },
        {
          "modality": "text",
          "value": "Re-reading and re-watching"
        },
        {
          "modality": "text",
          "value": "Listening and observing"
        }
      ],
      "correctIndex": 1,
      "explanation": "Interactive learning — teaching, debating, contributing — forces the deepest retrieval and negotiates your schema against other mental models.",
      "tags": [
        "learning-science",
        "modes"
      ],
      "uid": "lv2yya67vzbq"
    },
    {
      "id": "lt-cmp-passive-active",
      "shape": "comparison",
      "prompt": "Which builds durable long-term retention?",
      "correct": {
        "caption": "Active learning: recalling and practicing the material",
        "imageSearchTerm": "student writing practice quiz",
        "imagePrompt": "Photograph of a focused adult learner writing answers from memory at a desk, pen in hand, textbook closed beside them, warm study-lamp light, photorealistic, sense of effortful concentration"
      },
      "incorrect": {
        "caption": "Passive learning: re-reading notes and watching videos",
        "imageSearchTerm": "person reading textbook relaxed",
        "imagePrompt": "Photograph of a relaxed adult passively re-reading an open textbook on a couch, highlighter resting unused, soft ambient light, photorealistic, low-effort comfortable posture"
      },
      "explanation": "Passive learning (re-reading, watching) is useful for orientation but weak for retention. Active learning directly exercises and reinforces the neural pathways you need to recall later.",
      "tags": [
        "learning-science",
        "modes"
      ],
      "uid": "1etf2iafk57p2"
    },
    {
      "id": "lt-fact-forgetting-curve",
      "shape": "fact",
      "title": "The forgetting curve (Ebbinghaus, 1885)",
      "body": "German psychologist **Hermann Ebbinghaus** was among the first to study memory decay scientifically. Without review, we forget about **50% of new information within 30 minutes** and **70–80% within 24 hours**. This exponential decay is the **forgetting curve**.",
      "tags": [
        "memory",
        "forgetting-curve",
        "ebbinghaus"
      ],
      "studyGuideAnchor": "the-forgetting-curve-ebbinghaus-1885",
      "curatedDistractors": [
        "George Miller",
        "Ivan Pavlov",
        "B.F. Skinner"
      ],
      "illustration": {
        "imageSearchTerm": "declining curve graph",
        "imagePrompt": "An unlabeled line graph showing a steep downward curve, illustrating how quickly memory fades over time without review.",
        "alt": "The forgetting curve (Ebbinghaus, 1885)",
        "depictable": false,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:KletSlunecniHodiny.jpg",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-forgetting-curve.webp"
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    {
      "id": "lt-def-forgetting-curve",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Forgetting curve"
      },
      "definition": {
        "modality": "text",
        "value": "Ebbinghaus's finding that memory of new information decays exponentially over time without review, losing most of it within a day."
      },
      "tags": [
        "memory",
        "forgetting-curve"
      ],
      "uid": "134fd741bh9y8g"
    },
    {
      "id": "lt-num-forget-30min",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Share of new information forgotten within 30 minutes, without review"
      },
      "value": 50,
      "unit": "%",
      "tags": [
        "memory",
        "forgetting-curve"
      ],
      "uid": "18d1kaxkb092"
    },
    {
      "id": "lt-num-forget-24hr",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Share of new information forgotten within 24 hours, without review"
      },
      "value": 75,
      "unit": "%",
      "tags": [
        "memory",
        "forgetting-curve"
      ],
      "uid": "ctdd7yiwzzg2"
    },
    {
      "id": "lt-def-spaced-repetition",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Spaced repetition"
      },
      "definition": {
        "modality": "text",
        "value": "Distributing study sessions over expanding intervals, which produces far better retention than the same time spent cramming in one sitting."
      },
      "tags": [
        "memory",
        "spaced-repetition"
      ],
      "uid": "8i72kd5xnitj"
    },
    {
      "id": "lt-def-srs",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "SRS (Spaced Repetition Software)"
      },
      "definition": {
        "modality": "text",
        "value": "Software like Anki and SuperMemo that algorithmically schedules each review at the moment of maximum forgetting — the optimal interval."
      },
      "tags": [
        "memory",
        "spaced-repetition",
        "edtech"
      ],
      "curatedDistractors": [
        "Method of Loci (Memory Palace)",
        "Keyword Method",
        "Dual Coding Theory"
      ],
      "uid": "1c6eybaqkesm2"
    },
    {
      "id": "lt-pair-anki",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Anki / SuperMemo"
      },
      "sideB": {
        "modality": "text",
        "value": "SRS apps that schedule reviews at the optimal interval"
      },
      "tags": [
        "memory",
        "spaced-repetition",
        "edtech"
      ],
      "uid": "zodeve64qfdq"
    },
    {
      "id": "lt-proc-spacing-schedule",
      "shape": "procedure",
      "goal": "Schedule spaced-repetition reviews after first learning something",
      "steps": [
        "Study the material once, actively, on day 0.",
        "Review after 1 day.",
        "Review again after 3 days.",
        "Review again after 7 days.",
        "Review again after 14 days, extending intervals as recall strengthens."
      ],
      "notes": "Each review slows the forgetting curve. SRS apps automate this by timing reviews to the optimal interval — the moment you're about to forget.",
      "tags": [
        "memory",
        "spaced-repetition"
      ],
      "uid": "1vltqwa1pi29pa"
    },
    {
      "id": "lt-fact-testing-effect",
      "shape": "fact",
      "title": "The testing effect",
      "body": "Actively **retrieving** information from memory produces far stronger long-term retention than passively re-reading or re-watching. This is the **testing effect**, also called **retrieval practice** or the *production effect* — one of the most robust findings in cognitive psychology.",
      "tags": [
        "retrieval",
        "testing-effect"
      ],
      "factVariant": "image-heavy",
      "imageCaption": "Pulling facts OUT of memory beats putting them back in.",
      "illustration": {
        "imagePrompt": "Evocative photograph for a hero card: A student writing answers on a test paper",
        "imageSearchTerm": "student writing test",
        "alt": "A student writing answers on a test paper",
        "credit": "Pexels · Andy Barbour",
        "creditUrl": "https://www.pexels.com/photo/student-taking-exam-in-classroom-setting-31115182/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-testing-effect.webp"
      },
      "studyGuideAnchor": "the-testing-effect",
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    },
    {
      "id": "lt-def-retrieval-practice",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Retrieval practice"
      },
      "definition": {
        "modality": "text",
        "value": "Strengthening memory by actively recalling information rather than re-exposing yourself to it; the mechanism behind the testing effect."
      },
      "tags": [
        "retrieval",
        "testing-effect"
      ],
      "curatedDistractors": [
        "Spaced repetition",
        "Dual Coding Theory",
        "Interleaving"
      ],
      "uid": "1ez16z8cme198"
    },
    {
      "id": "lt-pair-roediger-butler",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Roediger & Butler (2011)"
      },
      "sideB": {
        "modality": "text",
        "value": "Retrieval practice's critical role in long-term retention"
      },
      "tags": [
        "retrieval",
        "testing-effect",
        "references"
      ],
      "uid": "whlk4l1w7le0f"
    },
    {
      "id": "lt-pair-karpicke-roediger",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Karpicke & Roediger (2008)"
      },
      "sideB": {
        "modality": "text",
        "value": "Science paper: the critical importance of retrieval for learning"
      },
      "tags": [
        "retrieval",
        "testing-effect",
        "references"
      ],
      "uid": "wujael1fs9v1z"
    },
    {
      "id": "lt-mcq-mit-implication",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "What practical implication does MIT Open Learning draw from the testing effect?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Administer low-stakes quizzes frequently"
        },
        {
          "modality": "text",
          "value": "Weight every quiz heavily in the final grade"
        },
        {
          "modality": "text",
          "value": "Keep quiz questions easy for everyone"
        },
        {
          "modality": "text",
          "value": "Replace short quizzes with guided re-reading"
        }
      ],
      "correctIndex": 0,
      "explanation": "MIT Open Learning summarizes the implication simply: give students frequent low-stakes quizzes, which trigger retrieval and solidify learning.",
      "tags": [
        "retrieval",
        "testing-effect",
        "edtech"
      ],
      "uid": "11hfph6pwe2au"
    },
    {
      "id": "lt-def-als",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Adaptive Learning System (ALS)"
      },
      "definition": {
        "modality": "text",
        "value": "Software that dynamically adjusts content difficulty, sequence, and modality based on ongoing learner performance data."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "wbsov9zyl2vj"
    },
    {
      "id": "lt-def-agentic-ai",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Agentic AI"
      },
      "definition": {
        "modality": "text",
        "value": "Autonomous AI that can plan, take actions, use tools, and pursue goals across multiple steps with minimal human intervention. In education it can orchestrate curriculum planning, content generation, assessment, and feedback in one loop."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "edwkvy1s43jd6"
    },
    {
      "id": "lt-def-generative-ai",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Generative AI (GenAI)"
      },
      "definition": {
        "modality": "text",
        "value": "AI systems that produce novel text, images, or audio. In education, GenAI enables dynamic content creation, conversational tutoring, and personalized feedback at scale."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1m4k1iwwivevs"
    },
    {
      "id": "lt-def-bkt",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Bayesian Knowledge Tracing (BKT)"
      },
      "definition": {
        "modality": "text",
        "value": "A probabilistic model used in intelligent tutoring systems to estimate the probability that a learner has mastered a skill, updating that estimate after each response."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1qivlq32a3rr5"
    },
    {
      "id": "lt-def-dkt",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Deep Knowledge Tracing (DKT)"
      },
      "definition": {
        "modality": "text",
        "value": "A recurrent neural network (LSTM) approach to knowledge tracing that models learner knowledge as a hidden state evolving with each interaction (Piech et al., 2015)."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1nxrq8i1bwky06"
    },
    {
      "id": "lt-def-knowledge-state",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Knowledge State"
      },
      "definition": {
        "modality": "text",
        "value": "A model representing what a specific learner currently knows and doesn't know within a domain, updated continuously by the system."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "tu5ncuhjqht6"
    },
    {
      "id": "lt-def-its",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Intelligent Tutoring System (ITS)"
      },
      "definition": {
        "modality": "text",
        "value": "Software that provides personalized instruction and feedback without a human teacher in the loop, using models of the domain, the learner, and pedagogy."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "j9c3vl13gjncz"
    },
    {
      "id": "lt-def-cognitive-tutor",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Cognitive Tutor"
      },
      "definition": {
        "modality": "text",
        "value": "An AI tutoring system developed at Carnegie Mellon that models student cognition and gives personalized hints and feedback within a specific domain, originally mathematics."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "wm6q4610bvp6"
    },
    {
      "id": "lt-def-algorithm-sequencing",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Algorithm-Based Sequencing"
      },
      "definition": {
        "modality": "text",
        "value": "Using ML models (often BKT or DKT) to predict learner knowledge states and determine the optimal next item to present."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "3srzb91uim2sn"
    },
    {
      "id": "lt-def-zero-shot",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Zero-Shot Learning (AI)"
      },
      "definition": {
        "modality": "text",
        "value": "An LLM's ability to perform a task it was not explicitly trained on, generalizing from broad pre-training — relevant to generating curriculum for rare or niche subjects."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1c1za2l1q6sixb"
    },
    {
      "id": "lt-def-affective-computing",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Affective Computing"
      },
      "definition": {
        "modality": "text",
        "value": "AI systems that detect and respond to learner emotions — frustration, boredom, curiosity — to adapt instruction accordingly."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "nk3pgy11la9y"
    },
    {
      "id": "lt-def-knowledge-graph",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Curriculum Graph / Knowledge Graph"
      },
      "definition": {
        "modality": "text",
        "value": "A structured representation of learning objectives and their dependencies, used by adaptive systems to find prerequisite relationships and optimal learning paths."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1qdgjpttduuqr"
    },
    {
      "id": "lt-def-ontology",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Ontology (Learning)"
      },
      "definition": {
        "modality": "text",
        "value": "A formal representation of knowledge and the relationships between concepts in a domain, used to structure curriculum graphs and content recommendations."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1ncf1v4kl09bk"
    },
    {
      "id": "lt-def-prompt-engineering",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Prompt Engineering"
      },
      "definition": {
        "modality": "text",
        "value": "Designing the inputs given to LLMs so they produce the desired instructional outputs — a practical skill for edtech builders working with foundation models."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1dpl28t1dojsf"
    },
    {
      "id": "lt-def-hitl",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Human-in-the-Loop (HITL)"
      },
      "definition": {
        "modality": "text",
        "value": "AI system design where humans review, approve, or override AI outputs before delivery — used in responsible edtech to catch errors and ensure quality."
      },
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "v6kuv4yhz2fs"
    },
    {
      "id": "lt-cmp-bkt-dkt",
      "shape": "comparison",
      "prompt": "Which model traces knowledge with a recurrent neural network rather than discrete per-skill probabilities?",
      "correct": {
        "caption": "Deep Knowledge Tracing (DKT): an LSTM holds learner knowledge as an evolving hidden state",
        "imageSearchTerm": "recurrent neural network diagram",
        "imagePrompt": "Clean schematic of an LSTM recurrent neural network unrolled over time, showing a hidden state passing from one time step to the next as learner responses feed in, labeled nodes, neutral palette, educational diagram style"
      },
      "incorrect": {
        "caption": "Bayesian Knowledge Tracing (BKT): a per-skill probability updated after each response",
        "imageSearchTerm": "bayesian probability diagram",
        "imagePrompt": "Clean schematic of a Bayesian knowledge-tracing model showing a single skill mastery probability updating after each student response, simple probability bars, neutral palette, educational diagram style"
      },
      "explanation": "BKT estimates a separate mastery probability per skill, updated Bayesian-style after each answer. DKT uses an LSTM that models knowledge as one evolving hidden state across all interactions.",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1mz2djkjbm7q0"
    },
    {
      "id": "lt-def-metacognition",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Metacognition"
      },
      "definition": {
        "modality": "text",
        "value": "Thinking about one's own thinking — awareness of one's learning process, knowledge gaps, and strategies. Tutors like Khanmigo foster it by asking students to explain their reasoning."
      },
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "10ehkeh1bh06yj"
    },
    {
      "id": "lt-def-differentiated-instruction",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Differentiated Instruction"
      },
      "definition": {
        "modality": "text",
        "value": "Tailoring content, process, or product to individual learner needs within a classroom setting — the human precursor to algorithmic personalization."
      },
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "pzhmrs1i6oii8"
    },
    {
      "id": "lt-def-personalized-learning",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Personalized Learning"
      },
      "definition": {
        "modality": "text",
        "value": "An instructional approach that tailors pace, content, sequence, and modality to the individual learner's needs, goals, and learning style."
      },
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "8dn81i11jqlii"
    },
    {
      "id": "lt-def-microlearning",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Microlearning"
      },
      "definition": {
        "modality": "text",
        "value": "Delivering content in short, focused bursts of 2–10 minutes, each built for a single learning objective. It exploits attention spans and mobile usage patterns."
      },
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1ntq2wh1ix20n7"
    },
    {
      "id": "lt-def-multimodal-learning",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Multimodal Learning"
      },
      "definition": {
        "modality": "text",
        "value": "Engaging multiple sensory channels — visual, auditory, kinesthetic — together to deepen encoding. Grounded in dual coding and cognitive load theories."
      },
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1gikjko1pguwzc"
    },
    {
      "id": "lt-def-pbl",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Problem-Based Learning (PBL)"
      },
      "definition": {
        "modality": "text",
        "value": "An approach where students learn by investigating and solving an authentic, complex, open-ended problem — rooted in Dewey's experiential philosophy."
      },
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1oq4o7o2vb7t8"
    },
    {
      "id": "lt-def-scaffolded-curriculum",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Scaffolded Curriculum"
      },
      "definition": {
        "modality": "text",
        "value": "A structured learning sequence that provides appropriate support at each level and fades assistance as competence grows — directly implementing Vygotsky's ZPD."
      },
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1fa6i9f15tnnnt"
    },
    {
      "id": "lt-def-cbe",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Competency-Based Education (CBE)"
      },
      "definition": {
        "modality": "text",
        "value": "An educational model where progression depends on demonstrating mastery of specific competencies, not on time spent in instruction."
      },
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1ukf4tg110xndw"
    },
    {
      "id": "lt-def-pck",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Pedagogical Content Knowledge (PCK)"
      },
      "definition": {
        "modality": "text",
        "value": "Shulman's 1986 concept: the specific knowledge teachers need about how to teach a particular subject, distinct from knowing the subject matter itself."
      },
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1y7n83g1sv06j0"
    },
    {
      "id": "lt-def-transfer",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Transfer of Learning"
      },
      "definition": {
        "modality": "text",
        "value": "Applying knowledge or skills learned in one context to new, different contexts. It is the ultimate goal of deep learning; shallow memorization often fails to transfer."
      },
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1vc99nunn4m6u"
    },
    {
      "id": "lt-def-working-memory",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Working Memory"
      },
      "definition": {
        "modality": "text",
        "value": "The cognitive system that temporarily holds and manipulates information during active processing (about 7±2 items). Cognitive load theory focuses on its limits."
      },
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "35ta9s59aw2o"
    },
    {
      "id": "lt-def-chunking",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Chunking"
      },
      "definition": {
        "modality": "text",
        "value": "Breaking complex information into smaller, more manageable units to reduce cognitive load and improve encoding."
      },
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1kk8olf1po18pt"
    },
    {
      "id": "lt-cmp-personalized-differentiated",
      "shape": "comparison",
      "prompt": "Which term is the algorithmic, learner-by-learner tailoring of pace, content, and sequence?",
      "correct": {
        "caption": "Personalized learning: pace, content, and sequence tuned to the individual learner",
        "imageSearchTerm": "personalized learning path",
        "imagePrompt": "Clean diagram of a personalized learning path: a single learner with an individual branching route through content nodes, adjusted by performance, neutral palette, educational diagram style"
      },
      "incorrect": {
        "caption": "Differentiated instruction: a teacher adapting tasks across groups within one classroom",
        "imageSearchTerm": "classroom group instruction",
        "imagePrompt": "Clean diagram of differentiated instruction: a teacher providing varied tasks to small groups within a single classroom, neutral palette, educational diagram style"
      },
      "explanation": "Personalized learning tailors to each individual, usually algorithmically. Differentiated instruction is its human classroom precursor — one teacher adapting across groups.",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "14swfvakxe5uy"
    },
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      "id": "lt-def-formative-assessment",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Formative Assessment"
      },
      "definition": {
        "modality": "text",
        "value": "Assessment during the learning process to provide feedback and adjust instruction. Low-stakes quizzes that trigger retrieval practice are an example."
      },
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1u7isser4dhbu"
    },
    {
      "id": "lt-def-summative-assessment",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Summative Assessment"
      },
      "definition": {
        "modality": "text",
        "value": "Evaluation of learning after instruction — exams, final projects — to grade outcomes. Contrasted with formative assessment."
      },
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1321z7ehf1c3q"
    },
    {
      "id": "lt-def-learner-analytics",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Learner Analytics"
      },
      "definition": {
        "modality": "text",
        "value": "The measurement, collection, analysis, and reporting of data about learners and their contexts in order to optimize learning."
      },
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "lx82z81bv1b6s"
    },
    {
      "id": "lt-def-kirkpatrick",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Kirkpatrick Model"
      },
      "definition": {
        "modality": "text",
        "value": "A four-level framework for evaluating training effectiveness: Reaction, then Learning, then Behavior, then Results."
      },
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "xglbea17f89y"
    },
    {
      "id": "lt-def-xapi",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "xAPI / Tin Can API"
      },
      "definition": {
        "modality": "text",
        "value": "A learning-data interoperability standard that captures experience statements across all learning contexts, not just the LMS."
      },
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "sm0yik1uwo5es"
    },
    {
      "id": "lt-def-mooc",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "MOOC (Massive Open Online Course)"
      },
      "definition": {
        "modality": "text",
        "value": "A large-scale online course open to unlimited participation. Coursera, edX, and Udemy pioneered the model."
      },
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "9gg1nd1poltj7"
    },
    {
      "id": "lt-def-stem-steam",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "STEM / STEAM"
      },
      "definition": {
        "modality": "text",
        "value": "Science, Technology, Engineering, (Arts), and Mathematics — disciplinary categories commonly addressed by edtech platforms."
      },
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "gjbkr8oku9hw"
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    {
      "id": "lt-def-edtech",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "EdTech"
      },
      "definition": {
        "modality": "text",
        "value": "Education technology — any technology used to facilitate or enhance learning."
      },
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
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    {
      "id": "lt-def-sdt",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Self-Determination Theory (SDT)"
      },
      "definition": {
        "modality": "text",
        "value": "Deci & Ryan's theory (1985) naming three basic psychological needs for intrinsic motivation: autonomy, competence, and relatedness. A framework for engagement and gamification design."
      },
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
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    },
    {
      "id": "lt-def-syllabus",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Syllabus / Curriculum Map"
      },
      "definition": {
        "modality": "text",
        "value": "A structured outline of learning objectives, content, sequence, and timeline for a course."
      },
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "wn1dt8s4sm2c"
    },
    {
      "id": "lt-cmp-formative-summative",
      "shape": "comparison",
      "prompt": "Which kind of assessment happens during learning to steer instruction?",
      "correct": {
        "caption": "Formative: low-stakes checks during learning that feed back into instruction",
        "imageSearchTerm": "classroom quick quiz",
        "imagePrompt": "Clean diagram of formative assessment: a learning loop where a quick low-stakes check feeds results back to adjust the next lesson, arrows forming a cycle, neutral palette, educational diagram style"
      },
      "incorrect": {
        "caption": "Summative: one high-stakes final exam graded after instruction is completely over",
        "imageSearchTerm": "final exam paper",
        "imagePrompt": "Clean diagram of summative assessment: a final exam at the end of a unit producing a grade, a straight timeline ending in a score, neutral palette, educational diagram style"
      },
      "explanation": "Formative assessment runs during learning to give feedback and adjust teaching. Summative assessment grades outcomes after instruction is finished.",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1qatfug1lk2i9s"
    },
    {
      "id": "lt-fact-behaviorism-intro",
      "shape": "fact",
      "title": "Behaviorism",
      "body": "**Behaviorism** holds that learning is observable behavior change produced by stimulus-response conditioning, reinforcement, and punishment. Its early-20th-century champions — **B.F. Skinner**, **Ivan Pavlov**, and **John Watson** — treated internal mental states as irrelevant: only what you can see and measure counts.",
      "tags": [
        "theory",
        "behaviorism",
        "learning-science"
      ],
      "studyGuideAnchor": "behaviorism",
      "illustration": {
        "imageSearchTerm": "Pavlov dog bell experiment",
        "imagePrompt": "A dog salivating beside a bell and a bowl, illustrating a classic stimulus-response conditioning experiment.",
        "alt": "Behaviorism",
        "depictable": true,
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      },
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    },
    {
      "id": "lt-def-operant-conditioning",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Operant conditioning"
      },
      "definition": {
        "modality": "text",
        "value": "Skinner's principle that behavior is shaped by its consequences — reinforcement and punishment — rather than by internal mental states."
      },
      "tags": [
        "theory",
        "behaviorism",
        "vocabulary"
      ],
      "curatedDistractors": [
        "Classical conditioning",
        "Assimilation",
        "Accommodation"
      ],
      "uid": "x06dx719kigxt"
    },
    {
      "id": "lt-pair-skinner",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "B.F. Skinner"
      },
      "sideB": {
        "modality": "text",
        "value": "Operant conditioning"
      },
      "tags": [
        "theory",
        "behaviorism",
        "theorist"
      ],
      "uid": "14w1m111jhq2a7"
    },
    {
      "id": "lt-pair-pavlov",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Ivan Pavlov"
      },
      "sideB": {
        "modality": "text",
        "value": "Stimulus-response conditioning"
      },
      "tags": [
        "theory",
        "behaviorism",
        "theorist"
      ],
      "uid": "l0u9cqaojeby"
    },
    {
      "id": "lt-pair-watson",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "John Watson"
      },
      "sideB": {
        "modality": "text",
        "value": "Early behaviorism"
      },
      "tags": [
        "theory",
        "behaviorism",
        "theorist"
      ],
      "uid": "hgt0621b57ex2"
    },
    {
      "id": "lt-fact-behaviorism-today",
      "shape": "fact",
      "title": "Behaviorism, gamified",
      "body": "Behaviorist principles underpin today's **gamification** — point systems, badges, streaks (Duolingo), and immediate feedback loops are reinforcement by another name. The **ADDIE** instructional-design model's military origins even trace back to Skinnerian operant conditioning.",
      "tags": [
        "theory",
        "behaviorism",
        "gamification"
      ],
      "factVariant": "image-heavy",
      "imageCaption": "Streaks, badges, points — Skinner's box, gamified.",
      "illustration": {
        "imagePrompt": "Evocative photograph for a hero card: A hand playing a colorful mobile game",
        "imageSearchTerm": "mobile game phone",
        "alt": "A hand playing a colorful mobile game",
        "credit": "Pexels · Beata Dudová",
        "creditUrl": "https://www.pexels.com/photo/person-playing-candy-crush-on-nokia-smartphone-228963/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-behaviorism-today.webp"
      },
      "studyGuideAnchor": "behaviorism-gamified",
      "uid": "1s2ae1dyoedir"
    },
    {
      "id": "lt-fact-behaviorism-terms",
      "shape": "fact",
      "title": "The behaviorist toolkit",
      "body": "Beyond reinforcement, behaviorism gave us **reinforcement schedules** (when rewards arrive), **shaping** (rewarding successive approximations toward a target behavior), and **stimulus generalization** (a response learned to one stimulus transfers to similar ones).",
      "tags": [
        "theory",
        "behaviorism",
        "vocabulary"
      ],
      "studyGuideAnchor": "the-behaviorist-toolkit",
      "illustration": {
        "imageSearchTerm": "Skinner box rat lever",
        "imagePrompt": "A laboratory rat pressing a lever inside a conditioning chamber, illustrating operant conditioning through reinforcement.",
        "alt": "The behaviorist toolkit",
        "depictable": true
      },
      "uid": "e7bs301xfefys"
    },
    {
      "id": "lt-fact-cognitivism-intro",
      "shape": "fact",
      "title": "Cognitivism",
      "body": "**Cognitivism** put the mind back in the picture. Where behaviorism saw a black box, cognitivists — **Jean Piaget**, **Jerome Bruner**, **Albert Bandura**, **George Miller** — studied the internal processes: schemas, attention, encoding, storage, retrieval. The mind actively *constructs* understanding.",
      "tags": [
        "theory",
        "cognitivism",
        "learning-science"
      ],
      "studyGuideAnchor": "cognitivism",
      "illustration": {
        "imageSearchTerm": "Cognitivism",
        "imagePrompt": "Cognitivism. **Cognitivism** put the mind back in the picture. Where behaviorism saw a black box, cognitivists — **Jean Piaget**, **Jerome Bruner**, **Albert Bandura**, **George Miller** — stud",
        "alt": "Cognitivism",
        "credit": "Pexels · meo",
        "creditUrl": "https://www.pexels.com/photo/photo-of-head-bust-print-artwork-724994/",
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      },
      "uid": "1voa7hmekqrke"
    },
    {
      "id": "lt-def-schema",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Schema"
      },
      "definition": {
        "modality": "text",
        "value": "A cognitive framework or category used to organize and interpret information."
      },
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "curatedDistractors": [
        "Assimilation",
        "Accommodation",
        "Equilibration"
      ],
      "uid": "u60j6nxk32v1"
    },
    {
      "id": "lt-def-assimilation",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Assimilation"
      },
      "definition": {
        "modality": "text",
        "value": "Integrating new information into an existing schema without changing the schema itself."
      },
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "uid": "dn719j1231c9h"
    },
    {
      "id": "lt-def-accommodation",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Accommodation"
      },
      "definition": {
        "modality": "text",
        "value": "Modifying an existing schema to incorporate contradictory new information."
      },
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "uid": "1oa8bg6ycps6a"
    },
    {
      "id": "lt-def-equilibration",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Equilibration"
      },
      "definition": {
        "modality": "text",
        "value": "The drive to balance assimilation and accommodation, resolving the tension between old schemas and new information."
      },
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "curatedDistractors": [
        "Adaptation",
        "Organization",
        "Decentration"
      ],
      "uid": "11w93x51330pt7"
    },
    {
      "id": "lt-cmp-assimilation-accommodation",
      "shape": "comparison",
      "prompt": "A child who calls every four-legged animal 'dog' meets a cat. Which response is accommodation?",
      "correct": {
        "caption": "Creating a new 'cat' schema distinct from 'dog'",
        "imageSearchTerm": "child learning cat dog",
        "imagePrompt": "Illustration of a child thoughtfully observing a cat and a dog side by side, mentally sorting them into two separate categories, soft educational storybook style, warm colors"
      },
      "incorrect": {
        "caption": "Filing the cat under the existing 'dog' schema",
        "imageSearchTerm": "child pointing at animal",
        "imagePrompt": "Illustration of a child confidently pointing at a cat and calling it a dog, cramming it into a single mental box labeled with paw prints, soft educational storybook style"
      },
      "explanation": "Accommodation modifies an existing schema to fit contradictory information — building a new 'cat' category. Cramming the cat into the 'dog' schema is assimilation.",
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "uid": "6a2w171j1qttl"
    },
    {
      "id": "lt-pair-miller",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "George Miller"
      },
      "sideB": {
        "modality": "text",
        "value": "Chunking / 7±2 rule"
      },
      "tags": [
        "theory",
        "cognitivism",
        "theorist"
      ],
      "uid": "uzjpdn180qc1"
    },
    {
      "id": "lt-proc-piaget-stages",
      "shape": "procedure",
      "goal": "Order Piaget's four stages of cognitive development",
      "steps": [
        "Sensorimotor",
        "Preoperational",
        "Concrete Operational",
        "Formal Operational"
      ],
      "notes": "Piaget's framework established that learners aren't passive recipients but active constructors of knowledge.",
      "tags": [
        "theory",
        "cognitivism",
        "theorist"
      ],
      "uid": "c8dafj1qgkka5"
    },
    {
      "id": "lt-fact-constructivism-intro",
      "shape": "fact",
      "title": "Constructivism",
      "body": "**Constructivism** holds that knowledge is *built* by the learner through active experience, not transmitted by a teacher. Context, culture, and social interaction shape what is learned. Its three poles: **Piaget** (cognitive), **Lev Vygotsky** (social), and **John Dewey** (pragmatic).",
      "tags": [
        "theory",
        "constructivism",
        "learning-science"
      ],
      "studyGuideAnchor": "constructivism",
      "illustration": {
        "imageSearchTerm": "Constructivism",
        "imagePrompt": "Constructivism. **Constructivism** holds that knowledge is *built* by the learner through active experience, not transmitted by a teacher. Context, culture, and social interaction shape what is le",
        "alt": "Constructivism",
        "credit": "Pexels · cottonbro studio",
        "creditUrl": "https://www.pexels.com/photo/persons-hand-on-yellow-paper-4965832/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-constructivism-intro.webp"
      },
      "uid": "1b3b8x5xye5pn"
    },
    {
      "id": "lt-def-zpd",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Zone of Proximal Development (ZPD)"
      },
      "definition": {
        "modality": "text",
        "value": "Vygotsky's gap between what a learner can do independently and what they can achieve with guidance from a 'more knowledgeable other'."
      },
      "tags": [
        "theory",
        "constructivism",
        "vocabulary"
      ],
      "curatedDistractors": [
        "Scaffolding",
        "Equilibration",
        "Metacognition"
      ],
      "uid": "xyyzp210b9woy"
    },
    {
      "id": "lt-def-scaffolding",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Scaffolding"
      },
      "definition": {
        "modality": "text",
        "value": "Temporary instructional support — hints, prompts, models, worked examples — that helps a learner progress through their ZPD, withdrawn as competence grows."
      },
      "tags": [
        "theory",
        "constructivism",
        "vocabulary"
      ],
      "uid": "etqvhaycfc42"
    },
    {
      "id": "lt-pair-vygotsky",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Lev Vygotsky"
      },
      "sideB": {
        "modality": "text",
        "value": "Zone of Proximal Development"
      },
      "tags": [
        "theory",
        "constructivism",
        "theorist"
      ],
      "uid": "zp95k1c9rguo"
    },
    {
      "id": "lt-pair-dewey",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "John Dewey"
      },
      "sideB": {
        "modality": "text",
        "value": "Learn by doing"
      },
      "tags": [
        "theory",
        "constructivism",
        "theorist"
      ],
      "uid": "ikthc613mpl56"
    },
    {
      "id": "lt-mcq-mko",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "In Vygotsky's ZPD, which source of guidance lets a learner exceed what they could do alone?"
      },
      "options": [
        {
          "modality": "text",
          "value": "A more knowledgeable other"
        },
        {
          "modality": "text",
          "value": "A peer at the same level"
        },
        {
          "modality": "text",
          "value": "Unaided trial and error"
        },
        {
          "modality": "text",
          "value": "A less experienced novice"
        }
      ],
      "correctIndex": 0,
      "explanation": "The 'more knowledgeable other' (MKO) — a teacher, parent, or more capable peer — provides the scaffolding that lets the learner operate within their zone of proximal development.",
      "tags": [
        "theory",
        "constructivism",
        "vocabulary"
      ],
      "uid": "13tjl25b4viyv"
    },
    {
      "id": "lt-fact-scaffolding-fading",
      "shape": "fact",
      "title": "Scaffolding and fading",
      "body": "Good scaffolding is **temporary by design**. As competence grows, the support is progressively withdrawn — a process called **fading**. Learning is optimized when a task falls *within* the ZPD: hard enough to need support, not so hard it causes frustration.",
      "tags": [
        "theory",
        "constructivism",
        "vocabulary"
      ],
      "studyGuideAnchor": "scaffolding-and-fading",
      "illustration": {
        "imageSearchTerm": "construction scaffolding building",
        "imagePrompt": "Construction scaffolding partially removed from the side of a building under renovation, revealing the finished wall beneath.",
        "alt": "Scaffolding and fading",
        "depictable": true,
        "credit": "Pexels · Nighttime view of a building under construction, wrapped in scaffolding and illuminated by bright lights.",
        "creditUrl": "https://www.pexels.com/photo/illuminated-building-under-construction-with-scaffolding-29106062/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-scaffolding-fading.webp"
      },
      "uid": "wwked1ptvj8n"
    },
    {
      "id": "lt-fact-blooms-taxonomy",
      "shape": "fact",
      "title": "Bloom's Taxonomy",
      "body": "**Bloom's Taxonomy** (Benjamin Bloom and colleagues, University of Chicago, **1956**) sorts cognitive skills into **six levels**, from lower-order recall up to higher-order thinking. It's the backbone of how we write learning objectives, design assessments, and calibrate difficulty.",
      "tags": [
        "theory",
        "blooms-taxonomy"
      ],
      "studyGuideAnchor": "bloom-s-taxonomy",
      "illustration": {
        "imageSearchTerm": "pyramid diagram levels",
        "imagePrompt": "An unlabeled six-tiered pyramid rising from a wide base to a narrow peak, representing increasing levels of cognitive skill.",
        "alt": "Bloom's Taxonomy",
        "depictable": false,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:Piramide_koloretsua.jpg",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-blooms-taxonomy.webp"
      },
      "uid": "v0jzgqxafamm"
    },
    {
      "id": "lt-def-blooms-taxonomy",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Bloom's Taxonomy"
      },
      "definition": {
        "modality": "text",
        "value": "A hierarchy of six cognitive skill levels, from lower-order to higher-order: in the revised version, Remember, Understand, Apply, Analyze, Evaluate, Create."
      },
      "tags": [
        "theory",
        "blooms-taxonomy"
      ],
      "curatedDistractors": [
        "SOLO Taxonomy",
        "Webb's Depth of Knowledge",
        "Gagné's Nine Events"
      ],
      "uid": "1ixjmzv1n0nxe1"
    },
    {
      "id": "lt-fact-blooms-revision",
      "shape": "fact",
      "title": "The 2001 Revision",
      "body": "In **2001**, Lorin **Anderson** and David **Krathwohl** revised Bloom's Taxonomy. They turned the noun levels into **verbs** (Knowledge became *Remember*), swapped the top two, and moved **Create** to the summit. The verbs make objectives and assessments far more actionable.",
      "tags": [
        "theory",
        "blooms-taxonomy"
      ],
      "studyGuideAnchor": "the-2001-revision",
      "illustration": {
        "imageSearchTerm": "mountain summit climber",
        "imagePrompt": "A climber reaching the summit of a mountain peak, symbolizing creativity as the highest level of thinking.",
        "alt": "The 2001 Revision",
        "depictable": false,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:Ewan_Hamilton.JPG",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-blooms-revision.webp"
      },
      "uid": "n5f58y1z062jy"
    },
    {
      "id": "lt-pair-knowledge-remember",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Knowledge (1956)"
      },
      "sideB": {
        "modality": "text",
        "value": "Remember (2001)"
      },
      "tags": [
        "blooms-taxonomy",
        "original-revised"
      ],
      "uid": "oqsdt413g68y0"
    },
    {
      "id": "lt-pair-comprehension-understand",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Comprehension (1956)"
      },
      "sideB": {
        "modality": "text",
        "value": "Understand (2001)"
      },
      "tags": [
        "blooms-taxonomy",
        "original-revised"
      ],
      "uid": "1mgma5bfwq899"
    },
    {
      "id": "lt-pair-synthesis-create",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Synthesis (1956)"
      },
      "sideB": {
        "modality": "text",
        "value": "Create (2001)"
      },
      "tags": [
        "blooms-taxonomy",
        "original-revised"
      ],
      "uid": "x3g2ir1er85pd"
    },
    {
      "id": "lt-pair-evaluation-evaluate",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Evaluation (1956)"
      },
      "sideB": {
        "modality": "text",
        "value": "Evaluate (2001)"
      },
      "tags": [
        "blooms-taxonomy",
        "original-revised"
      ],
      "uid": "oft8pg1shtulo"
    },
    {
      "id": "lt-pair-remember-verbs",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Remember"
      },
      "sideB": {
        "modality": "text",
        "value": "define, list, recall, identify"
      },
      "tags": [
        "blooms-taxonomy",
        "action-verbs"
      ],
      "uid": "yju9rk1i27wmw"
    },
    {
      "id": "lt-pair-apply-verbs",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Apply"
      },
      "sideB": {
        "modality": "text",
        "value": "use, execute, implement, solve"
      },
      "tags": [
        "blooms-taxonomy",
        "action-verbs"
      ],
      "uid": "1bwyxzbt723np"
    },
    {
      "id": "lt-pair-create-verbs",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Create"
      },
      "sideB": {
        "modality": "text",
        "value": "design, produce, construct, invent"
      },
      "tags": [
        "blooms-taxonomy",
        "action-verbs"
      ],
      "uid": "10adn6c1iy6djo"
    },
    {
      "id": "lt-proc-blooms-ladder",
      "shape": "procedure",
      "goal": "Climb Bloom's revised (2001) cognitive ladder from lowest to highest order",
      "steps": [
        "Remember — recall facts and basic concepts",
        "Understand — explain ideas in your own words",
        "Apply — use knowledge in a new situation",
        "Analyze — break material into parts and see how they relate",
        "Evaluate — judge, defend, or critique against criteria",
        "Create — combine parts into something new and original"
      ],
      "notes": "The 2001 revision swapped the top two levels and put Create — not Evaluate — at the summit.",
      "tags": [
        "blooms-taxonomy",
        "cognitive-levels"
      ],
      "uid": "yh88jfzq5l5d"
    },
    {
      "id": "lt-mcq-blooms-top",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "What is the highest level of the revised (2001) Bloom's Taxonomy?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Evaluate"
        },
        {
          "modality": "text",
          "value": "Create"
        },
        {
          "modality": "text",
          "value": "Remember"
        },
        {
          "modality": "text",
          "value": "Analyze"
        }
      ],
      "correctIndex": 1,
      "explanation": "The revision moved Create to the summit, ahead of Evaluate, to emphasize original production as the peak cognitive skill.",
      "tags": [
        "blooms-taxonomy",
        "cognitive-levels"
      ],
      "uid": "b6k3pc1eqrbi0"
    },
    {
      "id": "lt-fact-affective-domain",
      "shape": "fact",
      "title": "The Affective Domain",
      "body": "A second handbook (1964) covered the **affective domain** — attitudes, values, and motivations — across five levels: **Receiving, Responding, Valuing, Organizing, Characterizing.** Less discussed in edtech than the cognitive domain, but central to engagement design.",
      "tags": [
        "theory",
        "blooms-taxonomy",
        "affective-domain"
      ],
      "studyGuideAnchor": "the-affective-domain",
      "illustration": {
        "imageSearchTerm": "student engaged classroom",
        "imagePrompt": "A student's attentive, emotionally engaged expression while listening intently in a classroom setting.",
        "alt": "The Affective Domain",
        "depictable": false,
        "credit": "Pexels · Yan Krukau · Pexels License",
        "creditUrl": "https://www.pexels.com/photo/professor-standing-in-front-of-his-students-8197551/",
        "subject": "a wood-panelled university lecture hall; six students seated in rows with laptops and open books attend to a grey-bearded lecturer seen from behind at right",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-affective-domain.webp"
      },
      "uid": "y0ka5n1uxx59l"
    },
    {
      "id": "lt-mcq-affective-levels",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "Which set of five levels belongs to Bloom's affective domain?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Knowledge, Comprehension, Application, Analysis, Synthesis"
        },
        {
          "modality": "text",
          "value": "Analyzing, Designing, Developing, Implementing, Evaluating"
        },
        {
          "modality": "text",
          "value": "Receiving, Responding, Valuing, Organizing, Characterizing"
        },
        {
          "modality": "text",
          "value": "Imitation, Manipulation, Precision, Articulation, Naturalization"
        }
      ],
      "correctIndex": 2,
      "explanation": "The affective domain (1964) runs Receiving to Characterizing, charting how attitudes and values deepen.",
      "tags": [
        "blooms-taxonomy",
        "affective-domain"
      ],
      "uid": "1xnhnsdj3zajj"
    },
    {
      "id": "lt-fact-two-sigma",
      "shape": "fact",
      "title": "The 2 Sigma Problem",
      "body": "In **1984**, Bloom reported that students tutored **one-to-one** with mastery techniques scored **two standard deviations** higher than conventionally taught peers — the average tutored student beat **98%** of the control class. The catch: 1:1 tutoring doesn't scale.",
      "tags": [
        "theory",
        "two-sigma"
      ],
      "factVariant": "image-heavy",
      "imageCaption": "One-to-one tutoring lifts the average student two standard deviations.",
      "illustration": {
        "imagePrompt": "A tutor sitting beside a single student at a desk, pointing to a worksheet in a focused one-on-one lesson.",
        "imageSearchTerm": "tutor student desk",
        "alt": "An adult tutoring a child one-on-one at a laptop",
        "depictable": true,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:Avro_Tutor._Gosport._21-05-1937_MOD_45130346.jpg",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-two-sigma.webp"
      },
      "studyGuideAnchor": "the-2-sigma-problem",
      "uid": "1ot3hvt1isr017"
    },
    {
      "id": "lt-def-two-sigma-problem",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "The 2 Sigma Problem"
      },
      "definition": {
        "modality": "text",
        "value": "Bloom's 1984 challenge: one-to-one mastery tutoring lifts achievement by about two standard deviations, but is too costly to scale — so find a group method that matches it."
      },
      "tags": [
        "theory",
        "two-sigma"
      ],
      "uid": "1d4hibd16e7u3f"
    },
    {
      "id": "lt-def-mastery-learning",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Mastery learning"
      },
      "definition": {
        "modality": "text",
        "value": "An approach where students must reach a threshold (e.g. 90% on a test) before advancing; failures are treated as instructional gaps to correct, not student deficits."
      },
      "tags": [
        "theory",
        "two-sigma",
        "mastery-learning"
      ],
      "curatedDistractors": [
        "Differentiated Instruction",
        "Problem-Based Learning",
        "Personalized Learning"
      ],
      "uid": "1wx22bqn907yq"
    },
    {
      "id": "lt-mcq-mastery-threshold",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "In mastery learning, how is a student's failure to reach the threshold treated?"
      },
      "options": [
        {
          "modality": "text",
          "value": "As a bar set too high, not a student unable to clear it"
        },
        {
          "modality": "text",
          "value": "As an instructional gap to correct, not a student deficit"
        },
        {
          "modality": "text",
          "value": "As a need for more time on task, not more re-teaching"
        },
        {
          "modality": "text",
          "value": "As a flaw in the unit's sequencing, not in its teaching"
        }
      ],
      "correctIndex": 1,
      "explanation": "Mastery learning reframes failure as a feedback-corrective signal: the instruction missed, so fix the instruction and re-test.",
      "tags": [
        "two-sigma",
        "mastery-learning"
      ],
      "uid": "kgjkpmhvtwza"
    },
    {
      "id": "lt-mcq-two-sigma-scalability",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "Why did Bloom frame the two-sigma result as a 'problem'?"
      },
      "options": [
        {
          "modality": "text",
          "value": "One-to-one tutoring is economically unscalable"
        },
        {
          "modality": "text",
          "value": "The tutored gain appeared only among strong students"
        },
        {
          "modality": "text",
          "value": "Mastery learning in classrooms fell well short of a sigma"
        },
        {
          "modality": "text",
          "value": "The design lacked a conventional-classroom control"
        }
      ],
      "correctIndex": 0,
      "explanation": "The gain is huge but tutoring everyone 1:1 is unaffordable — Bloom challenged researchers to find a scalable group method that matches it. This is now the core pitch for AI tutoring.",
      "tags": [
        "two-sigma",
        "mastery-learning"
      ],
      "uid": "38ksps4tgqr4"
    },
    {
      "id": "lt-num-tutorial-effect",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Effect size of one-to-one tutorial instruction (Bloom's alterable variables)"
      },
      "value": 2,
      "unit": "sigma",
      "tags": [
        "effect-sizes",
        "two-sigma"
      ],
      "uid": "124px13dzseal"
    },
    {
      "id": "lt-num-reinforcement-effect",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Effect size of reinforcement (Bloom's alterable variables)"
      },
      "value": 1.2,
      "unit": "sigma",
      "tags": [
        "effect-sizes",
        "two-sigma"
      ],
      "uid": "jm2mkorf3xk0"
    },
    {
      "id": "lt-num-mastery-effect",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Effect size of mastery learning, feedback-corrective (Bloom's alterable variables)"
      },
      "value": 1,
      "unit": "sigma",
      "tags": [
        "effect-sizes",
        "two-sigma"
      ],
      "uid": "d4t0fs1h83pzs"
    },
    {
      "id": "lt-num-time-on-task-effect",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Effect size of student time on task (Bloom's alterable variables)"
      },
      "value": 1,
      "unit": "sigma",
      "tags": [
        "effect-sizes",
        "two-sigma"
      ],
      "uid": "1jloc2fw17ect"
    },
    {
      "id": "lt-num-cooperative-effect",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Effect size of cooperative learning (Bloom's alterable variables)"
      },
      "value": 0.8,
      "unit": "sigma",
      "tags": [
        "effect-sizes",
        "two-sigma"
      ],
      "uid": "8e8fzn1i70rm1"
    },
    {
      "id": "lt-num-homework-effect",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Effect size of graded homework (Bloom's alterable variables)"
      },
      "value": 0.8,
      "unit": "sigma",
      "tags": [
        "effect-sizes",
        "two-sigma"
      ],
      "uid": "2qs4zd67aq4r"
    },
    {
      "id": "lt-num-morale-effect",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Effect size of classroom morale (Bloom's alterable variables)"
      },
      "value": 0.6,
      "unit": "sigma",
      "tags": [
        "effect-sizes",
        "two-sigma"
      ],
      "uid": "whozgxmlyxmj"
    },
    {
      "id": "lt-def-flow",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Flow"
      },
      "definition": {
        "modality": "text",
        "value": "An optimal experience of complete psychological immersion in a task, marked by intense enjoyment and effortless concentration."
      },
      "tags": [
        "learning-science",
        "flow",
        "motivation"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1gjfcsk1cjw3qc"
    },
    {
      "id": "lt-fact-flow-challenge-skill",
      "shape": "fact",
      "title": "The challenge-skill balance",
      "body": "Mihaly **Csikszentmihalyi** described flow in 1975. Its condition is precise: task **challenge must match the learner's skill**. Too easy breeds **boredom**; too hard breeds **anxiety**; the balance produces flow.",
      "tags": [
        "learning-science",
        "flow",
        "motivation"
      ],
      "linkedItemIds": [
        "lt-mcq-flow-too-hard",
        "lt-def-flow"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "factVariant": "image-heavy",
      "imageCaption": "Challenge ≈ skill = flow. Too easy bores; too hard scares.",
      "illustration": {
        "imagePrompt": "An artist deeply absorbed in painting at an easel, completely focused and unaware of their surroundings.",
        "imageSearchTerm": "artist absorbed painting easel",
        "alt": "A person absorbed in painting at a desk",
        "depictable": true,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:Alm%C3%A9rio_-_cantor_pernambucano.jpg",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-flow-challenge-skill.webp"
      },
      "studyGuideAnchor": "the-challenge-skill-balance",
      "uid": "mo3976mla4u6"
    },
    {
      "id": "lt-mcq-flow-too-hard",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "In flow theory, what happens when a task's challenge far exceeds the learner's skill?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Apathy"
        },
        {
          "modality": "text",
          "value": "Boredom"
        },
        {
          "modality": "text",
          "value": "Anxiety"
        },
        {
          "modality": "text",
          "value": "Control"
        }
      ],
      "correctIndex": 2,
      "explanation": "Challenge above skill produces anxiety; challenge below skill produces boredom. Flow lives in the balance between the two.",
      "tags": [
        "learning-science",
        "flow",
        "motivation"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1c3soh51oovasz"
    },
    {
      "id": "lt-def-autotelic",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Autotelic activity"
      },
      "definition": {
        "modality": "text",
        "value": "An activity that is intrinsically rewarding — done for its own sake, not for an external payoff. The eighth hallmark of flow."
      },
      "tags": [
        "learning-science",
        "flow",
        "motivation"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "el766gfswgg0"
    },
    {
      "id": "lt-num-flow-mastery",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "In some studies, by what factor did flow-optimized learning accelerate mastery?"
      },
      "value": 2.3,
      "unit": "x",
      "tags": [
        "by-the-numbers",
        "flow",
        "learning-science"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "14vtxwwn0mfkw"
    },
    {
      "id": "lt-num-flow-burnout",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "By what percentage did flow-optimized environments reduce learner burnout in some studies?"
      },
      "value": 41,
      "unit": "%",
      "tags": [
        "by-the-numbers",
        "flow",
        "learning-science"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "oqqexkc2pwi0"
    },
    {
      "id": "lt-num-working-memory",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Roughly how many items can working memory hold at once (Cognitive Load Theory)?"
      },
      "value": 7,
      "unit": "items",
      "tags": [
        "by-the-numbers",
        "cognitive-load",
        "learning-science"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "wf02ij8cjj2x"
    },
    {
      "id": "lt-def-dual-coding",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Dual Coding Theory"
      },
      "definition": {
        "modality": "text",
        "value": "Paivio's idea that humans have two interconnected memory systems — verbal and visual — and learning improves when both are engaged at once."
      },
      "tags": [
        "learning-science",
        "dual-coding",
        "memory"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "3bft691qfybwz"
    },
    {
      "id": "lt-pair-paivio",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Allan Paivio (1971)"
      },
      "sideB": {
        "modality": "text",
        "value": "Dual Coding Theory"
      },
      "tags": [
        "learning-science",
        "dual-coding",
        "theorists"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1gwwdkb831rbt"
    },
    {
      "id": "lt-def-cognitive-load",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Cognitive Load Theory"
      },
      "definition": {
        "modality": "text",
        "value": "Sweller's theory (1988) that working memory has limited capacity, so instruction must manage how much mental load the material imposes."
      },
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "185x7l31pcej59"
    },
    {
      "id": "lt-def-intrinsic-load",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Intrinsic load"
      },
      "definition": {
        "modality": "text",
        "value": "The cognitive load that comes from the inherent complexity of the material itself — unavoidable, and set by the topic."
      },
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "12qf4pdypvpvn"
    },
    {
      "id": "lt-def-extraneous-load",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Extraneous load"
      },
      "definition": {
        "modality": "text",
        "value": "Cognitive load created by poor instructional design — unnecessary complexity that should be eliminated."
      },
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "lyf8xm1ewhwxq"
    },
    {
      "id": "lt-def-germane-load",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Germane load"
      },
      "definition": {
        "modality": "text",
        "value": "Cognitive effort directed at building mental schemas — the productive load that designers should maximize."
      },
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "o2a04ge8nb28"
    },
    {
      "id": "lt-cmp-intrinsic-extraneous-load",
      "shape": "comparison",
      "prompt": "Which kind of cognitive load should an instructional designer work to eliminate?",
      "correct": {
        "caption": "Extraneous load: distracting clutter from poor design choices — cut it",
        "imageSearchTerm": "cluttered confusing interface",
        "imagePrompt": "A messy, overloaded slide crammed with mismatched fonts, redundant labels, and clashing graphics, conveying confusion and wasted attention, flat editorial illustration style"
      },
      "incorrect": {
        "caption": "Intrinsic load: the topic's inherent difficulty — unavoidable",
        "imageSearchTerm": "complex equation chalkboard",
        "imagePrompt": "A clean chalkboard with a genuinely hard mathematical derivation, conveying inherent, necessary complexity rather than clutter, flat editorial illustration style"
      },
      "explanation": "Extraneous load comes from bad design and should be removed. Intrinsic load is the material's built-in difficulty. Germane load — effort spent building schemas — is the goal to maximize.",
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "taxkns9ax0zc"
    },
    {
      "id": "lt-def-connectivism",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Connectivism"
      },
      "definition": {
        "modality": "text",
        "value": "Siemens and Downes's 'learning theory for the digital age': learning is the process of creating connections between nodes in a network."
      },
      "tags": [
        "theory",
        "connectivism",
        "digital-age"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "curatedDistractors": [
        "Behaviorism",
        "Cognitivism",
        "Constructivism"
      ],
      "uid": "1d9vuni1tgwk7m"
    },
    {
      "id": "lt-pair-siemens-downes",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Siemens & Downes (2004–05)"
      },
      "sideB": {
        "modality": "text",
        "value": "Connectivism"
      },
      "tags": [
        "theory",
        "connectivism",
        "theorists"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "zog7521xhm6qy"
    },
    {
      "id": "lt-fact-know-where",
      "shape": "fact",
      "title": "Know-where beats know-that",
      "body": "Connectivism holds that **knowing where to find information** matters more than what you currently know. Knowledge is **distributed across networks** — people, books, databases, AI — not stored only in one mind. Prescient for the LLM era.",
      "tags": [
        "theory",
        "connectivism",
        "digital-age"
      ],
      "linkedItemIds": [
        "lt-mcq-connectivism-value"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "studyGuideAnchor": "know-where-beats-know-that",
      "illustration": {
        "imageSearchTerm": "person surrounded floating books",
        "imagePrompt": "A person at the center of floating books, blank glowing screens, and network lines, representing distributed knowledge sources.",
        "alt": "Know-where beats know-that",
        "depictable": false,
        "credit": "Pexels · A man in eyeglasses and suit surrounded by floating books in a dramatic, dimly lit setting.",
        "creditUrl": "https://www.pexels.com/photo/man-in-a-dark-room-throwing-books-9758181/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-know-where.webp"
      },
      "uid": "1tu4of2v53vuy"
    },
    {
      "id": "lt-mcq-connectivism-value",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "Per connectivism, where does educational value shift in the AI era?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Toward know-how — building skills that transfer across tools"
        },
        {
          "modality": "text",
          "value": "Toward know-that — retaining facts a model might get wrong"
        },
        {
          "modality": "text",
          "value": "Toward know-why — explaining the causes behind each fact"
        },
        {
          "modality": "text",
          "value": "Toward know-where — accessing and evaluating information"
        }
      ],
      "correctIndex": 3,
      "explanation": "Connectivism argues the capacity to know where to find, evaluate, and contextualize information outweighs memorized facts — especially when an LLM can answer anything instantly.",
      "tags": [
        "theory",
        "connectivism",
        "digital-age"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1o77ytm7t1tpa"
    },
    {
      "id": "lt-mcq-connectivism-gap",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "What gap did connectivism claim older theories failed to address?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Learning that is carried in the body, in movement and gesture",
          "short": "Learning carried in the body"
        },
        {
          "modality": "text",
          "value": "Learning that occurs outside the human mind, in networks and systems",
          "short": "Learning in networks and systems"
        },
        {
          "modality": "text",
          "value": "Learning that stays tacit, in habits too automatic to describe",
          "short": "Learning that stays tacit"
        },
        {
          "modality": "text",
          "value": "Learning that arises from emotion, in feelings and motivation",
          "short": "Learning driven by emotion"
        }
      ],
      "correctIndex": 1,
      "explanation": "Siemens and Downes argued behaviorism, cognitivism, and constructivism all locate learning inside the individual, missing learning that happens in networks, organizations, and digital systems.",
      "tags": [
        "theory",
        "connectivism",
        "digital-age"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "10p93lv6kov0h"
    },
    {
      "id": "lt-pair-gagne",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Robert Gagné (1965)"
      },
      "sideB": {
        "modality": "text",
        "value": "Nine Events of Instruction"
      },
      "tags": [
        "instructional-design",
        "gagne",
        "theorists"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "kcba61xc2z6j"
    },
    {
      "id": "lt-proc-gagne-nine-events",
      "shape": "procedure",
      "goal": "Run Gagné's Nine Events of Instruction in order",
      "steps": [
        "Gain attention (reception)",
        "Inform learners of objectives (expectancy)",
        "Stimulate recall of prior learning (retrieval)",
        "Present the content (selective perception)",
        "Provide learning guidance (semantic encoding)",
        "Elicit performance (responding)",
        "Provide feedback (reinforcement)",
        "Assess performance (retrieval)",
        "Enhance retention and transfer (generalization)"
      ],
      "notes": "Gagné's nine events read like a design checklist for a well-architected tutoring session — each can be orchestrated by an LLM tutor at scale.",
      "tags": [
        "instructional-design",
        "gagne",
        "lesson-design"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1ni8ur21g8k7aa"
    },
    {
      "id": "lt-mcq-gagne-outcomes",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "Which is one of Gagné's five categories of learning outcomes?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Interpersonal skills"
        },
        {
          "modality": "text",
          "value": "Verbal reasoning"
        },
        {
          "modality": "text",
          "value": "Perceptual abilities"
        },
        {
          "modality": "text",
          "value": "Cognitive strategies"
        }
      ],
      "correctIndex": 3,
      "explanation": "Gagné's five outcome categories are verbal information, intellectual skills, cognitive strategies, motor skills, and attitudes — each requiring a different type of instruction.",
      "tags": [
        "instructional-design",
        "gagne",
        "lesson-design"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1o68rav5ymbt9"
    },
    {
      "id": "lt-fact-gagne-five-outcomes",
      "shape": "fact",
      "title": "Five kinds of learning outcome",
      "body": "Gagné's *Conditions of Learning* named five outcome categories: **verbal information, intellectual skills, cognitive strategies, motor skills, and attitudes**. His point — each kind requires a different type of instruction.",
      "tags": [
        "instructional-design",
        "gagne",
        "lesson-design"
      ],
      "linkedItemIds": [
        "lt-mcq-gagne-outcomes"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "studyGuideAnchor": "five-kinds-of-learning-outcome",
      "illustration": {
        "imageSearchTerm": "five abstract symbols row",
        "imagePrompt": "Five distinct abstract shapes arranged in a row without text, representing different categories of learning outcomes.",
        "alt": "Five kinds of learning outcome",
        "depictable": false,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:%D0%9F%D1%8F%D1%82%D1%8C_%D1%81%D0%BA%D1%83%D0%BB%D1%8C%D0%BF%D1%82%D1%83%D1%80_2H1A5527WI.jpg",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-gagne-five-outcomes.webp"
      },
      "uid": "1x0edbx27wpa7"
    },
    {
      "id": "lt-mcq-gagne-first-event",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "What is the first of Gagné's Nine Events of Instruction?"
      },
      "options": [
        {
          "modality": "text",
          "value": "State objectives"
        },
        {
          "modality": "text",
          "value": "Stimulate recall"
        },
        {
          "modality": "text",
          "value": "Gain attention"
        },
        {
          "modality": "text",
          "value": "Present content"
        }
      ],
      "correctIndex": 2,
      "explanation": "The sequence opens by gaining attention (reception), then informs learners of objectives, and ends by enhancing retention and transfer.",
      "tags": [
        "instructional-design",
        "gagne",
        "lesson-design"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1bol9jn1tysxgx"
    },
    {
      "id": "lt-def-udl",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Universal Design for Learning (UDL)"
      },
      "definition": {
        "modality": "text",
        "value": "A neuroscience-based curriculum framework (Rose, CAST) that builds flexibility into learning from the outset rather than adding accommodations afterward."
      },
      "tags": [
        "instructional-design",
        "udl",
        "accessibility"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "curatedDistractors": [
        "ADDIE",
        "Dick & Carey Model",
        "Merrill's Principles of Instruction"
      ],
      "uid": "y9tu8o1o8z4hs"
    },
    {
      "id": "lt-pair-udl-representation",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Representation (UDL)"
      },
      "sideB": {
        "modality": "text",
        "value": "The 'what' — multiple means of presenting content"
      },
      "tags": [
        "instructional-design",
        "udl",
        "accessibility"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "13p0498y5ia8c"
    },
    {
      "id": "lt-pair-udl-action",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Action & Expression (UDL)"
      },
      "sideB": {
        "modality": "text",
        "value": "The 'how' — multiple ways to demonstrate knowledge"
      },
      "tags": [
        "instructional-design",
        "udl",
        "accessibility"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1ke9ax51jiajyb"
    },
    {
      "id": "lt-pair-udl-engagement",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Engagement (UDL)"
      },
      "sideB": {
        "modality": "text",
        "value": "The 'why' — multiple means of motivation and interest"
      },
      "tags": [
        "instructional-design",
        "udl",
        "accessibility"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1975m4r1ocltkh"
    },
    {
      "id": "lt-mcq-udl-principle",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "Which UDL principle addresses the 'why' of learning?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Representation"
        },
        {
          "modality": "text",
          "value": "Retention"
        },
        {
          "modality": "text",
          "value": "Engagement"
        },
        {
          "modality": "text",
          "value": "Action & Expression"
        }
      ],
      "correctIndex": 2,
      "explanation": "UDL's three principles map to what (Representation), how (Action & Expression), and why (Engagement) — the why being motivation and interest.",
      "tags": [
        "instructional-design",
        "udl",
        "accessibility"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1dukimud3y68q"
    },
    {
      "id": "lt-def-method-of-loci",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Method of Loci (Memory Palace)"
      },
      "definition": {
        "modality": "text",
        "value": "An ancient technique that places items to be memorized at spatial locations along a familiar mental journey; walking the path retrieves them in sequence."
      },
      "tags": [
        "memory",
        "mnemonics",
        "method-of-loci"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "1qh7h66kw4n3u"
    },
    {
      "id": "lt-def-keyword-method",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Keyword Method"
      },
      "definition": {
        "modality": "text",
        "value": "A language-learning mnemonic that links a foreign word's sound to a memorable image which bridges to the translation."
      },
      "tags": [
        "memory",
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        "keyword-method"
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      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "curatedDistractors": [
        "Method of Loci (Memory Palace)",
        "Chunking",
        "Dual Coding Theory"
      ],
      "uid": "1rgxsg0y7wwx4"
    },
    {
      "id": "lt-fact-mnemonic-images",
      "shape": "fact",
      "title": "Why vivid images stick",
      "body": "**Mnemonic images** — concrete, vivid mental pictures — are far easier to recall than abstract words. Linking a target word to a similar-sounding or similar-meaning image fires both the verbal and visual systems at once: **dual coding in action**.",
      "tags": [
        "memory",
        "mnemonics",
        "dual-coding"
      ],
      "linkedItemIds": [
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      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "studyGuideAnchor": "why-vivid-images-stick",
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    },
    {
      "id": "lt-mcq-loci-leverage",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "What memory strength does the method of loci exploit?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Spatial-episodic memory"
        },
        {
          "modality": "text",
          "value": "Procedural motor memory"
        },
        {
          "modality": "text",
          "value": "Verbal-semantic memory"
        },
        {
          "modality": "text",
          "value": "Phonological working memory"
        }
      ],
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      "explanation": "By placing information along a familiar route, the method of loci leverages the brain's strong spatial-episodic memory — which is why memory champions use it to memorize thousands of digits.",
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        "memory",
        "mnemonics",
        "method-of-loci"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
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    },
    {
      "id": "lt-pair-memory-palace-origin",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Ancient Greece and Rome"
      },
      "sideB": {
        "modality": "text",
        "value": "Origin of the method of loci"
      },
      "tags": [
        "memory",
        "mnemonics",
        "method-of-loci"
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "uid": "yal0yv1h8cotp"
    },
    {
      "id": "lt-fact-addie-origin",
      "shape": "fact",
      "title": "Where ADDIE came from",
      "body": "**ADDIE** was developed in **1975** at **Florida State University's** Center for Educational Technology — for the **U.S. Army**. Decades later it remains the dominant **instructional systems design (ISD)** framework worldwide. The name is just an acronym for its five phases.",
      "tags": [
        "instructional-design",
        "addie",
        "history"
      ],
      "studyGuideAnchor": "where-addie-came-from",
      "curatedDistractors": [
        "Indiana University",
        "University of Michigan",
        "Ohio State University"
      ],
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        "imageSearchTerm": "military training classroom",
        "imagePrompt": "Soldiers seated in a training classroom, receiving structured instructional material from an instructor.",
        "alt": "Where ADDIE came from",
        "depictable": true,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:Catalpa_tree_Shiloh_NMP.jpg",
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      "id": "lt-def-addie",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "ADDIE"
      },
      "definition": {
        "modality": "text",
        "value": "An instructional systems design framework structured as five phases: Analyze, Design, Develop, Implement, and Evaluate."
      },
      "tags": [
        "instructional-design",
        "addie"
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      "curatedDistractors": [
        "SAM (Successive Approximation Model)",
        "Dick & Carey Model",
        "Merrill's Principles of Instruction"
      ],
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    },
    {
      "id": "lt-proc-addie",
      "shape": "procedure",
      "goal": "Work through the five ADDIE phases in order",
      "steps": [
        "Analyze — identify learning goals, audience, existing knowledge, and constraints.",
        "Design — define objectives, assessment strategy, content sequencing, and modalities.",
        "Develop — build the actual content, activities, and assessments.",
        "Implement — deliver the instruction to learners.",
        "Evaluate — assess effectiveness, both during development and after delivery."
      ],
      "notes": "In modern practice, evaluation feeds back into every other phase rather than waiting until the end.",
      "tags": [
        "instructional-design",
        "addie"
      ],
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    },
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      "id": "lt-pair-addie-analyze",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Analyze (ADDIE)"
      },
      "sideB": {
        "modality": "text",
        "value": "Identify goals, audience, prior knowledge, and constraints"
      },
      "tags": [
        "instructional-design",
        "addie"
      ],
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    },
    {
      "id": "lt-pair-addie-design",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Design (ADDIE)"
      },
      "sideB": {
        "modality": "text",
        "value": "Define objectives, assessment, sequencing, and modalities"
      },
      "tags": [
        "instructional-design",
        "addie"
      ],
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    },
    {
      "id": "lt-pair-addie-develop",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Develop (ADDIE)"
      },
      "sideB": {
        "modality": "text",
        "value": "Build the content, activities, and assessments"
      },
      "tags": [
        "instructional-design",
        "addie"
      ],
      "uid": "1vuxtbd1mmc477"
    },
    {
      "id": "lt-cmp-addie-waterfall-iterative",
      "shape": "comparison",
      "prompt": "Which describes modern ADDIE practice?",
      "correct": {
        "caption": "Iterative — evaluation feeds back into every phase",
        "imageSearchTerm": "iterative feedback loop diagram",
        "imagePrompt": "Clean schematic of a circular, iterative design process with five labeled nodes connected by feedback arrows looping back from a central evaluation node to every other stage, flat vector style, calm professional palette"
      },
      "incorrect": {
        "caption": "Strict waterfall — finish each phase before the next",
        "imageSearchTerm": "waterfall process diagram",
        "imagePrompt": "Clean schematic of a strict linear waterfall process, five stacked stages cascading downward with single one-way arrows and no return paths, flat vector style, muted palette"
      },
      "explanation": "ADDIE began as a waterfall model — complete each phase before the next — but modern ADDIE is fully iterative, with evaluation looping back into all phases.",
      "tags": [
        "instructional-design",
        "addie"
      ],
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    },
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      "id": "lt-fact-addie-rigidity",
      "shape": "fact",
      "title": "The rigidity criticism",
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      "tags": [
        "instructional-design",
        "addie",
        "critique"
      ],
      "studyGuideAnchor": "the-rigidity-criticism",
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        "imageSearchTerm": "rigid fixed assembly line",
        "imagePrompt": "A rigid, straight metal assembly line with fixed sequential stations in a factory, evoking an inflexible step-by-step process.",
        "alt": "The rigidity criticism",
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        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:Commer_bus_reg_EC_634.jpg",
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    },
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      "id": "lt-pair-dick-carey",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Dick & Carey Model (1978)"
      },
      "sideB": {
        "modality": "text",
        "value": "Systems-theory approach; more prescriptive than ADDIE"
      },
      "tags": [
        "instructional-design",
        "frameworks"
      ],
      "uid": "1ndrgq91wyuyeb"
    },
    {
      "id": "lt-pair-sam",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "SAM (2012)"
      },
      "sideB": {
        "modality": "text",
        "value": "Rapid, agile prototyping; explicitly iterative"
      },
      "tags": [
        "instructional-design",
        "frameworks"
      ],
      "uid": "1oieqwc4dtu04"
    },
    {
      "id": "lt-pair-merrill",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Merrill's Principles (2002)"
      },
      "sideB": {
        "modality": "text",
        "value": "Task-centered 'first principles' of effective design"
      },
      "tags": [
        "instructional-design",
        "frameworks"
      ],
      "uid": "1ciegjxgj45zj"
    },
    {
      "id": "lt-pair-ubd",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Understanding by Design (1998)"
      },
      "sideB": {
        "modality": "text",
        "value": "Backward design — start from desired outcomes"
      },
      "tags": [
        "instructional-design",
        "frameworks"
      ],
      "uid": "kvn6kcc4tamk"
    },
    {
      "id": "lt-def-backward-design",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Backward design"
      },
      "definition": {
        "modality": "text",
        "value": "Wiggins and McTighe's approach in Understanding by Design: start from the desired learning outcomes, then work back to assessments and instruction."
      },
      "tags": [
        "instructional-design",
        "frameworks"
      ],
      "curatedDistractors": [
        "Action Mapping",
        "SAM (Successive Approximation Model)",
        "Merrill's Principles of Instruction"
      ],
      "uid": "1bjos9se1difk"
    },
    {
      "id": "lt-def-action-mapping",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Action Mapping"
      },
      "definition": {
        "modality": "text",
        "value": "Cathy Moore's 2008 performance-focused method that strips out 'nice to know' content and designs around what learners must actually do."
      },
      "tags": [
        "instructional-design",
        "frameworks"
      ],
      "curatedDistractors": [
        "Backward design",
        "SAM (Successive Approximation Model)",
        "Dick & Carey Model"
      ],
      "uid": "1qzurohhm2jxf"
    },
    {
      "id": "lt-mcq-backward-design",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "Which framework is built on 'backward design'?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Successive Approximation Model (Allen)"
        },
        {
          "modality": "text",
          "value": "Understanding by Design (Wiggins & McTighe)"
        },
        {
          "modality": "text",
          "value": "Systematic Design of Instruction (Dick & Carey)"
        },
        {
          "modality": "text",
          "value": "First Principles of Instruction (Merrill)"
        }
      ],
      "correctIndex": 1,
      "explanation": "Understanding by Design (1998) is the framework that defines backward design — starting from desired learning outcomes and working back.",
      "tags": [
        "instructional-design",
        "frameworks"
      ],
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    },
    {
      "id": "lt-def-socratic-method",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "The Socratic method"
      },
      "definition": {
        "modality": "text",
        "value": "Teaching through guided, probing questions rather than direct answers, so the learner constructs the insight independently — yielding deeper encoding."
      },
      "tags": [
        "instructional-design",
        "socratic"
      ],
      "curatedDistractors": [
        "Direct instruction",
        "Lecture method",
        "Problem-Based Learning (PBL)"
      ],
      "uid": "8brdrd1uydohn"
    },
    {
      "id": "lt-cmp-direct-socratic",
      "shape": "comparison",
      "prompt": "Which is the Socratic approach to tutoring?",
      "correct": {
        "caption": "Ask probing questions that lead the learner to the insight",
        "imageSearchTerm": "teacher asking student questions",
        "imagePrompt": "Warm illustration of a tutor leaning in and posing a question, a thought bubble forming over the student as they work toward an answer themselves, soft natural light, flat editorial style"
      },
      "incorrect": {
        "caption": "Hand the learner the fully finished answer directly, right away",
        "imageSearchTerm": "lecture handing notes",
        "imagePrompt": "Illustration of an instructor handing a sheet with the completed answer straight to a passive student, one-way transfer, flat editorial style, cooler palette"
      },
      "explanation": "A Socratic tutor asks probing questions so the learner builds the insight independently — producing deeper encoding and stronger schema formation than simply being told.",
      "tags": [
        "instructional-design",
        "socratic"
      ],
      "uid": "g6l8t11bdbzn3"
    },
    {
      "id": "lt-fact-khanmigo-socratic",
      "shape": "fact",
      "title": "Khanmigo, by design",
      "body": "Sal Khan built **Khanmigo** to embody Socratic principles: it guides students *through* their learning rather than just handing over answers. That operationalizes a constructivist insight — knowledge a learner builds is more durable than knowledge merely received.",
      "tags": [
        "instructional-design",
        "socratic",
        "edtech"
      ],
      "studyGuideAnchor": "khanmigo-by-design",
      "curatedDistractors": [
        "Luis von Ahn",
        "Sebastian Thrun",
        "Sam Altman"
      ],
      "illustration": {
        "imageSearchTerm": "Socratic tutor student dialogue",
        "imagePrompt": "An adult mentor and a young student sitting face to face, the mentor gesturing thoughtfully mid-question, evoking a Socratic dialogue between tutor and learner.",
        "alt": "Khanmigo, by design",
        "depictable": false,
        "credit": "AI-generated (gpt-image-1.5)",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-khanmigo-socratic.webp"
      },
      "uid": "1fqjdbq1jlr8ga"
    },
    {
      "id": "lt-fact-brave-new-words",
      "shape": "fact",
      "title": "Brave New Words",
      "body": "**Brave New Words: How AI Will Revolutionize Education (and Why That's a Good Thing)** (2024) by **Salman Khan** is part memoir, part technology manifesto. It frames AI not as a cheating threat but as the most powerful potential equalizer in education history — a way to give every student a world-class personal tutor.",
      "tags": [
        "edtech",
        "brave-new-words",
        "ai"
      ],
      "studyGuideAnchor": "brave-new-words",
      "illustration": {
        "imageSearchTerm": "Salman Khan Brave New Words",
        "imagePrompt": "A hardcover nonfiction book with a blank cover resting on a wooden desk beside a laptop and a cup of coffee, evoking a technology-and-education manifesto.",
        "alt": "Brave New Words",
        "depictable": true
      },
      "uid": "ysb0kccpb5j0"
    },
    {
      "id": "lt-def-personalization-problem",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "The personalization problem"
      },
      "definition": {
        "modality": "text",
        "value": "Great education requires understanding where a specific learner is, what they know, how they learn, and what engages them — historically only possible with expensive private tutors. Khan argues AI can democratize this at scale."
      },
      "tags": [
        "edtech",
        "brave-new-words",
        "personalization"
      ],
      "curatedDistractors": [
        "The ethical framework",
        "The contrarian review",
        "Beyond K-12"
      ],
      "uid": "m4pjwxmnz1yj"
    },
    {
      "id": "lt-fact-chatgpt-panic",
      "shape": "fact",
      "title": "After November 2022",
      "body": "When **ChatGPT** launched in **November 2022**, many educators' first response was panic about cheating. Khan's reframing runs against that reaction: rather than a threat to academic integrity, he casts conversational AI as a tutor that can finally personalize learning for everyone.",
      "tags": [
        "edtech",
        "brave-new-words",
        "ai"
      ],
      "studyGuideAnchor": "after-november-2022",
      "illustration": {
        "imageSearchTerm": "teacher worried student laptop",
        "imagePrompt": "A teacher sitting at a desk, looking with concern at a laptop screen while grading papers, evoking early anxiety about AI-assisted cheating in classrooms.",
        "alt": "After November 2022",
        "depictable": false,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:English_teacher.jpg",
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      },
      "uid": "1lq4qd913jtkxj"
    },
    {
      "id": "lt-pair-diamond-age",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "The Diamond Age (Neal Stephenson)"
      },
      "sideB": {
        "modality": "text",
        "value": "An AI tutor for a poor girl becomes her greatest educational resource"
      },
      "tags": [
        "edtech",
        "brave-new-words",
        "sci-fi"
      ],
      "uid": "1rwgnn5e6wezf"
    },
    {
      "id": "lt-pair-enders-game",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Ender's Game"
      },
      "sideB": {
        "modality": "text",
        "value": "Personalized, challenge-driven simulation learning"
      },
      "tags": [
        "edtech",
        "brave-new-words",
        "sci-fi"
      ],
      "uid": "1oyal9mdg7z8u"
    },
    {
      "id": "lt-pair-fun-they-had",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Asimov's \"The Fun They Had\""
      },
      "sideB": {
        "modality": "text",
        "value": "A child finds a classroom of other children an exotic concept"
      },
      "tags": [
        "edtech",
        "brave-new-words",
        "sci-fi"
      ],
      "uid": "4ml8z1b4u8g9"
    },
    {
      "id": "lt-mcq-three-inspirations",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "Which of the three works opening Brave New Words imagines an AI tutor transforming a poor girl's life?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The Fun They Had"
        },
        {
          "modality": "text",
          "value": "Ender's Game"
        },
        {
          "modality": "text",
          "value": "Snow Crash"
        },
        {
          "modality": "text",
          "value": "The Diamond Age"
        }
      ],
      "correctIndex": 3,
      "explanation": "Khan opens with three touchstones: The Diamond Age, where an AI tutor transforms a poor girl's life; Ender's Game, for challenge-driven simulation learning; and Asimov's \"The Fun They Had\", where a future child finds a classroom of peers exotic. Snow Crash, also by Stephenson, is not among them.",
      "tags": [
        "edtech",
        "brave-new-words",
        "sci-fi"
      ],
      "uid": "1plhl5v1vq9r49"
    },
    {
      "id": "lt-fact-equity-engine",
      "shape": "fact",
      "title": "AI as equity engine",
      "body": "Khan argues AI can address historical education inequity by giving students in under-resourced communities access to individualized tutoring equivalent to what wealthy families buy in private instruction. This directly targets **Bloom's 2 Sigma Problem** — the gap between tutored and classroom learners.",
      "tags": [
        "edtech",
        "brave-new-words",
        "equity"
      ],
      "studyGuideAnchor": "ai-as-equity-engine",
      "illustration": {
        "imageSearchTerm": "one-on-one tutoring versus classroom",
        "imagePrompt": "A single tutor sitting closely with one student at a table, contrasted in the background with a large, crowded classroom of many students and one teacher, illustrating the gap between individual and group instruction.",
        "alt": "AI as equity engine",
        "depictable": false,
        "credit": "AI-generated (gpt-image-1.5)",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-equity-engine.webp"
      },
      "uid": "mf3ccrznx1c9"
    },
    {
      "id": "lt-def-khanmigo",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Khanmigo"
      },
      "definition": {
        "modality": "text",
        "value": "An AI tutoring assistant built on GPT-4 in collaboration with OpenAI. The name plays on \"Khan\" and the Spanish \"conmigo\" (\"with me\"). It uses the Socratic method, guides step-by-step, and never simply delivers answers."
      },
      "tags": [
        "edtech",
        "khanmigo",
        "ai"
      ],
      "curatedDistractors": [
        "MagicSchool AI",
        "Duolingo Max",
        "Google NotebookLM"
      ],
      "uid": "171b75xnbd14v"
    },
    {
      "id": "lt-fact-khanmigo-name",
      "shape": "fact",
      "title": "Khan + conmigo",
      "body": "**Khanmigo** is a play on \"Khan\" and the Spanish word **conmigo** — \"with me.\" The pun captures the pitch: a tutor that learns alongside the student rather than lecturing at them. It was built on **GPT-4** with OpenAI as Khan Academy's proof of concept.",
      "tags": [
        "edtech",
        "khanmigo",
        "ai"
      ],
      "studyGuideAnchor": "khan-conmigo",
      "curatedDistractors": [
        "Coursera",
        "Duolingo",
        "Udacity"
      ],
      "illustration": {
        "imageSearchTerm": "student tutor learning together",
        "imagePrompt": "A student and a mentor working side by side at a table with papers and a laptop between them, evoking companionship in learning.",
        "alt": "Khan + conmigo",
        "depictable": false,
        "credit": "AI-generated (gpt-image-1.5)",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-khanmigo-name.webp"
      },
      "uid": "1qe37zk1i9gm60"
    },
    {
      "id": "lt-pair-conmigo",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "conmigo"
      },
      "sideB": {
        "modality": "text",
        "value": "Spanish for \"with me\" — the root of Khanmigo's name"
      },
      "tags": [
        "edtech",
        "khanmigo",
        "vocabulary"
      ],
      "uid": "54clm119k0ub7"
    },
    {
      "id": "lt-cmp-cheating-vs-equalizer",
      "shape": "comparison",
      "prompt": "How does Brave New Words frame AI in education?",
      "correct": {
        "caption": "AI as an equalizer: a world-class personal tutor for every student",
        "imageSearchTerm": "student tablet tutor learning",
        "imagePrompt": "Warm photograph of a young student smiling while learning one-on-one with a friendly AI tutor interface on a tablet, soft natural light, sense of access and possibility, photorealistic"
      },
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        "caption": "AI as a dangerous cheating threat to be banned from every classroom",
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        "imagePrompt": "Photograph of a classroom with a phone hidden under a desk during a test, tense mood, a red 'no devices' sign on the wall, photorealistic, suggesting suspicion and prohibition"
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      "explanation": "After ChatGPT's 2022 launch many educators saw a cheating threat. Khan reframes AI as the most powerful potential equalizer in education history.",
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      "title": "Beyond K-12",
      "body": "Khan does not confine the argument to schools. **Brave New Words** explores AI's implications for **college admissions**, the **workplace**, and **civic participation** — treating personalized AI as infrastructure for learning across a whole life, not just the K-12 years.",
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        "imagePrompt": "An adult professional studying on a laptop at an office desk, evoking lifelong learning that extends beyond the K-12 classroom.",
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        "depictable": false,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:Adult_Swim_creators.jpg",
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      "id": "lt-fact-ethical-framework",
      "shape": "fact",
      "title": "The ethical framework",
      "body": "Khan does not pretend the technology is finished. He explicitly acknowledges current AI's limits — **hallucination**, **bias**, and **privacy** risks — and argues for a responsible deployment approach rather than uncritical adoption.",
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        "depictable": false,
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        "creditUrl": "https://commons.wikimedia.org/wiki/File:Anton_Romako_-_Am_Wasserfall.jpg",
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    {
      "id": "lt-fact-warner-critique",
      "shape": "fact",
      "title": "The contrarian review",
      "body": "Reception was mixed. **John Warner**, writing in *Engaged Education*, argues the book \"makes no real attempt to grapple with the implications of its own argument\" — leaning on faith in technology rather than rigorous evidence. The tension between **technology optimism** and **pedagogical rigor** sits at the center of today's edtech debates.",
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        "edtech",
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        "criticism"
      ],
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        "depictable": false,
        "credit": "AI-generated (gpt-image-1.5)",
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      "uid": "110vm5rsnrnfx"
    },
    {
      "id": "lt-fact-ai-taxonomy",
      "shape": "fact",
      "title": "Mapping the AI-in-education space",
      "body": "The AI-in-education landscape splits by **function**: AI tutors (1:1 conversational instruction), teacher tools (lesson planning, grading), language learning, research assistants, enterprise/workforce upskilling, assessment & analytics, micro/game learning, and LMS infrastructure. Each category has its own leading players.",
      "tags": [
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      ],
      "factVariant": "image-heavy",
      "imageCaption": "Tutors, teacher tools, language apps — the new AI-in-education map.",
      "illustration": {
        "imagePrompt": "A wide classroom scene with students using tablets and laptops in small groups, evoking the broad landscape of AI tools used across different parts of education.",
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        "alt": "Students learning with laptops in a library",
        "depictable": false,
        "credit": "Pexels · Students in a Japanese classroom using tablets for learning. Modern educational technology in Tokyo.",
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        "value": "AI Tutors"
      },
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        "modality": "text",
        "value": "Adaptive, conversational 1:1 instruction (Khanmigo, Synthesis, LearnLM)"
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    {
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      "shape": "pair",
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        "modality": "text",
        "value": "Teacher Tools"
      },
      "sideB": {
        "modality": "text",
        "value": "Lesson planning, rubric generation, admin reduction (MagicSchool, Diffit)"
      },
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    },
    {
      "id": "lt-pair-language-duolingo",
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      "sideA": {
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        "value": "Language Learning"
      },
      "sideB": {
        "modality": "text",
        "value": "Adaptive vocabulary and conversation practice (Duolingo, Lingokids)"
      },
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    {
      "id": "lt-pair-research-notebooklm",
      "shape": "pair",
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        "value": "Research Assistants"
      },
      "sideB": {
        "modality": "text",
        "value": "Document synthesis, multi-source knowledge (NotebookLM, Perplexity)"
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        "value": "Enterprise / Workforce"
      },
      "sideB": {
        "modality": "text",
        "value": "Upskilling and corporate training (Sana, Coursera+Udemy, Multiverse)"
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    {
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        "value": "Assessment & Analytics"
      },
      "sideB": {
        "modality": "text",
        "value": "Progress tracking, formative assessment (Gradescope, Eedi, MagicQuizzes)"
      },
      "tags": [
        "taxonomy",
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      ],
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    },
    {
      "id": "lt-pair-gamelearning-kahoot",
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        "value": "Micro / Game Learning"
      },
      "sideB": {
        "modality": "text",
        "value": "Game-based, challenge-driven learning (Kahoot, Blooket, Synthesis Teams)"
      },
      "tags": [
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      ],
      "uid": "1lc18wz1jofkfl"
    },
    {
      "id": "lt-mcq-taxonomy-notebooklm",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "Which category does Google NotebookLM belong to?"
      },
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          "value": "Research Assistants"
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      "id": "lt-fact-khanmigo",
      "shape": "fact",
      "title": "Khanmigo",
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        "credit": "NEC Corporation of America (Openverse) · by 2.0",
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        "subject": "Two teenage students, a girl in light blue and a boy in purple, typing on laptops side by side at a table in a school library, bookshelves blurred behind",
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        "value": "K-12 students using Khanmigo in the 2024–25 academic year"
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      "id": "lt-mcq-khanmigo-method",
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      "prompt": {
        "modality": "text",
        "value": "What teaching approach does Khanmigo use?"
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        {
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      ],
      "correctIndex": 0,
      "explanation": "Khanmigo uses the Socratic method, guiding students with questions rather than supplying the answer.",
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    {
      "id": "lt-fact-duolingo-birdbrain",
      "shape": "fact",
      "title": "Duolingo: BirdBrain and Max",
      "body": "Duolingo's proprietary **BirdBrain** model orchestrates, sequences, and personalizes lessons from a learner's performance history. The freemium **Duolingo Max** tier (GPT-4 powered) adds roleplay and 'Explain My Answer', plus a **Lily** chat feature that recreates dynamic conversation practice. AI also lets Duolingo scale its language library without the human-content bottleneck.",
      "tags": [
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      "factVariant": "image-heavy",
      "imageCaption": "AI sequences every lesson to keep you in the flow corridor.",
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        "imagePrompt": "A person using a smartphone language-learning app at a cafe table, colorful abstract speech-bubble shapes floating above the screen, evoking personalized AI-driven language practice, no legible text or logos.",
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        "alt": "'Learn languages' in letter tiles beside a phone",
        "depictable": false,
        "credit": "Pexels · Discover the Kazakh language learning app on a smartphone next to a classic fountain pen and notebook.",
        "creditUrl": "https://www.pexels.com/photo/modern-learning-app-display-with-fountain-pen-32764502/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-duolingo-birdbrain.webp"
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        "modality": "text",
        "value": "Duolingo BirdBrain"
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      "sideB": {
        "modality": "text",
        "value": "Proprietary AI that sequences and personalizes lessons from performance history"
      },
      "tags": [
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    {
      "id": "lt-fact-magicschool",
      "shape": "fact",
      "title": "MagicSchool AI",
      "body": "**MagicSchool AI** reached **2+ million educators** and 4,000+ schools within its first year, backed by a **$45M Series B** (2025). It is evolving from a 'collection of tools' into a 'connected teaching system' — Studio Mode, MagicQuizzes, Class Writing Feedback, and Knowledge. Safety, district alignment, and LMS integrations are its core differentiators.",
      "tags": [
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      "studyGuideAnchor": "magicschool-ai",
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        "alt": "MagicSchool AI",
        "depictable": false,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:English_Teacher,_April_2022.jpg",
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      "id": "lt-fact-synthesis",
      "shape": "fact",
      "title": "Synthesis",
      "body": "**Synthesis** was built for the SpaceX employee school and founded by Chrisman Frank. It's an adaptive **K-6 math** platform with a voice-guided interface and visual math representations, favoring conceptual understanding over rote drilling. A family subscription runs **~$99/year**. It's on pace for **$10M+ revenue** in 2025, with subscribed students up **4.5x** year-over-year.",
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        "credit": "Pexels · Young girl in pajamas using a tablet with headphones, nestled in cozy bedroom environment.",
        "creditUrl": "https://www.pexels.com/photo/child-using-tablet-in-bed-10566191/",
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        "value": "Adaptive learning system"
      },
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        "value": "Software that adjusts the content, sequence, and difficulty of instruction in real time based on each learner's performance history."
      },
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        "value": "Where did Synthesis originate?"
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        },
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      "explanation": "Synthesis was built for the SpaceX employee school and founded by Chrisman Frank.",
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      "title": "Google NotebookLM",
      "body": "**NotebookLM** ingests documents — PDFs, YouTube, web pages — and builds a research-grounded knowledge base for chat, synthesis, and multi-modal output (text, audio podcasts, slides). Its key trait: outputs are **grounded in the provided sources**, which reduces hallucination for domain-specific synthesis. Builders use it to spin up custom learning assistants without fine-tuning a model.",
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      "studyGuideAnchor": "google-notebooklm",
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        "credit": "Pexels · Adult man focused on documents while working remotely at home with laptop and headphones.",
        "creditUrl": "https://www.pexels.com/photo/man-working-remotely-from-home-6285270/",
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        "value": "A computer system that delivers individualized instruction and feedback, modeling both the subject and the learner's evolving understanding to guide them like a one-on-one tutor."
      },
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      "curatedDistractors": [
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      "title": "What the meta-analysis shows",
      "body": "Broad meta-analysis finds that adaptive AI systems can **cut learning time by 30–50%** while **improving outcomes by 15–25%** versus traditional instruction. Visual and kinesthetic learners show the most substantial gains. The big caveat: most studies are short-term and subject-specific — long-term effects on motivation, metacognition, and transfer are still open questions.",
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        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:120116-F-YZ446-023_(6802990001).jpg",
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      "title": "The LearnLM RCT",
      "body": "In Google/Eedi Labs' 2025 randomized trial, 165 students aged 13–15 were assigned to a human tutor, an AI tutor (**LearnLM**), or static hints. Human tutors approved 76.4% of LearnLM's responses with little or no edits. LearnLM students hit a **66% success rate** on subsequent harder topics — versus **61%** (human tutor) and **56%** (static hints).",
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        "imagePrompt": "Two side-by-side tutoring scenes: a human tutor working with a teenage student on one side, and the same student using a tablet-based AI tutor on the other, evoking a research comparison.",
        "alt": "The LearnLM RCT",
        "depictable": false,
        "credit": "Pexels · Student and tutor engaged in a study session with notes and stationery.",
        "creditUrl": "https://www.pexels.com/photo/a-tutor-teaching-a-student-5311450/",
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        "value": "Human-tutor group's success rate in the LearnLM RCT"
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      "value": 61,
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    },
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      "id": "lt-num-statichints-success",
      "shape": "numeric",
      "prompt": {
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        "value": "Static-hints group's success rate in the LearnLM RCT"
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      "value": 56,
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      "tags": [
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    {
      "id": "lt-fact-tutor-copilot",
      "shape": "fact",
      "title": "Stanford's Tutor CoPilot",
      "body": "Stanford's 2024 **Tutor CoPilot** RCT put an AI tool coaching 1,000 elementary students' human tutors in real time. Students with AI-assisted tutors were **4 percentage points** more likely to reach topic mastery — and gains rose to **9 points** for students paired with less-experienced tutors. The AI raised the *floor* of tutor quality.",
      "tags": [
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      "studyGuideAnchor": "stanford-s-tutor-copilot",
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        "imagePrompt": "An elementary tutor sitting with a young student, glancing at a small screen displaying a real-time coaching suggestion during the session, no legible text.",
        "alt": "Stanford's Tutor CoPilot",
        "depictable": false,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:Avro_621_Trainer_3-view_NACA_Aircraft_Circular_No.119.jpg",
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      },
      "uid": "1ezoyat1k8yls7"
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    {
      "id": "lt-mcq-tutor-copilot-floor",
      "shape": "mcq",
      "prompt": {
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        "value": "Who benefited most from Stanford's Tutor CoPilot?"
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        {
          "modality": "text",
          "value": "Students paired with the most experienced tutors"
        },
        {
          "modality": "text",
          "value": "Students paired with less-experienced tutors"
        },
        {
          "modality": "text",
          "value": "Students working with the AI tutor on their own"
        },
        {
          "modality": "text",
          "value": "Students whose tutors were coached only after sessions"
        }
      ],
      "correctIndex": 1,
      "explanation": "Gains reached up to 9 points for students with less-experienced tutors — the AI raised the floor of tutor quality.",
      "tags": [
        "evidence",
        "research"
      ],
      "uid": "1a01m201gl1c94"
    },
    {
      "id": "lt-fact-brookings",
      "shape": "fact",
      "title": "The Brookings finding",
      "body": "A 2026 Brookings Institution analysis reported that students using the AI tutor achieved **more than double** the learning gains relative to the pre-test baseline compared with the control group. Pair this with a 2025 Scientific Reports RCT where AI tutoring outperformed in-class active learning at an effect size of 0.73 — high by educational standards.",
      "tags": [
        "evidence",
        "research"
      ],
      "studyGuideAnchor": "the-brookings-finding",
      "illustration": {
        "imageSearchTerm": "student workbook classroom desk",
        "imagePrompt": "A student writing in a workbook at a classroom desk with sunlight through the window, evoking measurable academic learning gains.",
        "alt": "The Brookings finding",
        "depictable": false,
        "credit": "Pexels · Student desk with many textbooks and stationery placed against whiteboard in light classroom in school",
        "creditUrl": "https://www.pexels.com/photo/school-desk-with-copybooks-in-modern-classroom-5905435/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-brookings.webp"
      },
      "uid": "1k0o2ec1aocas4"
    },
    {
      "id": "lt-fact-market-size",
      "shape": "fact",
      "title": "The adaptive-learning market",
      "body": "The adaptive learning platform market was valued at **$1.72 billion in 2025** and is expected to reach **$5.47 billion by 2032**. Global EdTech investment hit **$2.6 billion in 2025**, up roughly 11% over 2024, with capital concentrating in AI-enabled products and workforce-aligned platforms.",
      "tags": [
        "market",
        "investment"
      ],
      "studyGuideAnchor": "the-adaptive-learning-market",
      "illustration": {
        "imageSearchTerm": "rising bar chart growth",
        "imagePrompt": "An upward-trending bar chart rendered as abstract glowing blocks increasing in height against a dark background, evoking market growth, no visible numbers or text.",
        "alt": "The adaptive-learning market",
        "depictable": false,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:Rising,_Shangri-La_Toronto,_11_March_2016_-_02.jpg",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-market-size.webp"
      },
      "uid": "1jdjb401ssimko"
    },
    {
      "id": "lt-num-market-2025",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Value of the adaptive learning platform market in 2025"
      },
      "value": 1720000000,
      "unit": "USD",
      "tags": [
        "market",
        "investment"
      ],
      "uid": "1klg4hf1c2iv0h"
    },
    {
      "id": "lt-num-market-2032",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Projected adaptive learning platform market value by 2032"
      },
      "value": 5470000000,
      "unit": "USD",
      "tags": [
        "market",
        "investment"
      ],
      "uid": "7nibazzeerhl"
    },
    {
      "id": "lt-num-edtech-investment-2025",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Total global EdTech investment in 2025"
      },
      "value": 2600000000,
      "unit": "USD",
      "tags": [
        "market",
        "investment"
      ],
      "uid": "1yvu6s8qssgg8"
    },
    {
      "id": "lt-num-workday-sana",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Price Workday paid to acquire Sana"
      },
      "value": 1100000000,
      "unit": "USD",
      "tags": [
        "market",
        "investment"
      ],
      "uid": "1e8ldj1xxo6r3"
    },
    {
      "id": "lt-num-coursera-udemy",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Value of the Coursera–Udemy all-stock acquisition (Dec 2025)"
      },
      "value": 2500000000,
      "unit": "USD",
      "tags": [
        "market",
        "investment"
      ],
      "uid": "koyrn1v5v8hb"
    },
    {
      "id": "lt-fact-sector-split",
      "shape": "fact",
      "title": "Where the 2025 money went",
      "body": "By deal volume, 2025 EdTech investment split: **workforce training 38%**, **K-12 36%**, **post-secondary 22%**, and **early childhood 4%**. Notable deals: Workday acquired Sana for $1.1B, and Coursera's $2.5B all-stock acquisition of Udemy created a combined platform of 290 million learners and 18,000 enterprise customers.",
      "tags": [
        "market",
        "investment"
      ],
      "studyGuideAnchor": "where-the-2025-money-went",
      "illustration": {
        "imageSearchTerm": "office handshake business deal",
        "imagePrompt": "Two business professionals shaking hands in a modern office, evoking a corporate acquisition or investment deal.",
        "alt": "Where the 2025 money went",
        "depictable": false,
        "credit": "Pexels · Close-up of a business handshake between two professionals over an office desk with documents.",
        "creditUrl": "https://www.pexels.com/photo/handshake-in-close-up-8837510/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-sector-split.webp"
      },
      "uid": "yvkmv61fbzbra"
    },
    {
      "id": "lt-cmp-engagement-vs-outcomes",
      "shape": "comparison",
      "prompt": "What do disciplined 2026 EdTech investors increasingly demand a platform prove?",
      "correct": {
        "caption": "Measurable learning outcomes — gains on real assessments",
        "imageSearchTerm": "student test score improvement chart",
        "imagePrompt": "Clean data-visualization of a bar chart showing pre-test versus post-test learning gains rising sharply, a checkmark beside the higher bar, professional muted palette, education-analytics aesthetic"
      },
      "incorrect": {
        "caption": "Engagement metrics — daily active users and time-in-app",
        "imageSearchTerm": "app engagement dashboard daily active users",
        "imagePrompt": "Clean dashboard illustration showing daily-active-user and time-in-app engagement graphs trending up, a small caution marker, muted analytics palette, product-metrics aesthetic"
      },
      "explanation": "2026 capital is disciplined: it favors workflow-embedded, agentic AI that delivers measurable outcomes, not just engagement metrics like time-in-app.",
      "tags": [
        "market",
        "investment"
      ],
      "uid": "7x2d2u1af0u4q"
    },
    {
      "id": "lt-fact-2026-projections",
      "shape": "fact",
      "title": "The 2026 outlook",
      "body": "Capital in 2026 is expected to stay disciplined — favoring **workflow-embedded, agentic AI** and solutions that deliver **measurable outcomes** over raw engagement. Owl Ventures projects the global education market will surpass **$10 trillion by 2030**, the long backdrop against which today's AI-platform race is playing out.",
      "tags": [
        "market",
        "investment"
      ],
      "studyGuideAnchor": "the-2026-outlook",
      "illustration": {
        "imageSearchTerm": "world map growth forecast",
        "imagePrompt": "An abstract world map rendered in glowing lines with an upward arrow sweeping across continents, evoking a long-term global market forecast, no visible text.",
        "alt": "The 2026 outlook",
        "depictable": false,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:Beyonce_-_The_Formation_World_Tour,_at_Wembley_Stadium_in_London,_England.jpg",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-2026-projections.webp"
      },
      "uid": "18h8yilz3vwv3"
    },
    {
      "id": "lt-fact-lms-lineage",
      "shape": "fact",
      "title": "A century of teaching machines",
      "body": "The **LMS** lineage runs back further than the web. It starts with Sidney Pressey's mechanical **teaching machine** (1924), continues through **PLATO** computer-based training (1960, Dr. Donald Bitzer), web-based systems in the 1990s, **Moodle**'s open-source release (2002), the cloud/SaaS era (2010s), the xAPI/analytics era, and AI-integrated systems in the 2020s.",
      "tags": [
        "edtech",
        "lms",
        "history"
      ],
      "studyGuideAnchor": "a-century-of-teaching-machines",
      "illustration": {
        "imageSearchTerm": "Pressey mechanical teaching machine",
        "imagePrompt": "A vintage 1920s mechanical teaching machine with dials, levers, and a small viewing window, resembling an early typewriter-like device, sitting on a wooden desk.",
        "alt": "A century of teaching machines",
        "depictable": true,
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/lt-fact-lms-lineage.webp",
        "credit": "Pexels · File:Phil Pressey with Idaho.JPG",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:Phil_Pressey_with_Idaho.JPG"
      },
      "uid": "5wd5g71u0kdbh"
    },
    {
      "id": "lt-proc-lms-evolution",
      "shape": "procedure",
      "goal": "Trace the evolution of the learning management system, earliest to latest",
      "steps": [
        "Pressey's mechanical teaching machine (1924)",
        "PLATO computer-based training (1960, Donald Bitzer)",
        "Web-based LMS (1990s)",
        "Moodle open-source LMS (2002)",
        "Cloud / SaaS LMS era (2010s)",
        "xAPI / analytics era (mid-2010s)",
        "AI-integrated systems (2020s)"
      ],
      "notes": "The throughline is the same instinct across a century: automate the delivery, tracking, and adaptation of instruction.",
      "tags": [
        "edtech",
        "lms",
        "history"
      ],
      "uid": "1s7t3pwfxyq90"
    },
    {
      "id": "lt-num-lms-years",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Year Sidney Pressey built his mechanical teaching machine"
      },
      "value": 1924,
      "unit": "year",
      "tags": [
        "lms",
        "history",
        "edtech"
      ],
      "uid": "frqamjvve7fd"
    },
    {
      "id": "lt-num-plato",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Year PLATO computer-based training launched (Donald Bitzer)"
      },
      "value": 1960,
      "unit": "year",
      "tags": [
        "lms",
        "history",
        "edtech"
      ],
      "uid": "1vf9wrr1rhyud1"
    },
    {
      "id": "lt-num-scorm",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Year the SCORM interoperability standard was introduced"
      },
      "value": 2001,
      "unit": "year",
      "tags": [
        "lms",
        "standards",
        "edtech"
      ],
      "uid": "7a5vputbf88e"
    },
    {
      "id": "lt-num-moodle",
      "shape": "numeric",
      "prompt": {
        "modality": "text",
        "value": "Year Moodle was released as an open-source LMS"
      },
      "value": 2002,
      "unit": "year",
      "tags": [
        "lms",
        "history",
        "edtech"
      ],
      "uid": "4aebswfr388g"
    },
    {
      "id": "lt-def-scorm",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "SCORM"
      },
      "definition": {
        "modality": "text",
        "value": "Sharable Content Object Reference Model (2001) — the original interoperability standard letting content work across different LMSs. Tracks completions and quiz scores only."
      },
      "tags": [
        "standards",
        "lms",
        "vocabulary"
      ],
      "uid": "1fmjr1m171eje6"
    },
    {
      "id": "lt-def-lrs",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "LRS (Learning Record Store)"
      },
      "definition": {
        "modality": "text",
        "value": "The backend database that stores xAPI statements — a portable, durable repository of all learning activity across systems."
      },
      "tags": [
        "standards",
        "lms",
        "vocabulary"
      ],
      "curatedDistractors": [
        "SCORM",
        "LMS (Learning Management System)",
        "Learning Tools Interoperability (LTI)"
      ],
      "uid": "aqdk2rtt2u2h"
    },
    {
      "id": "lt-pair-scorm-tracks",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "SCORM"
      },
      "sideB": {
        "modality": "text",
        "value": "Tracks completions and quiz scores only"
      },
      "tags": [
        "standards",
        "lms"
      ],
      "uid": "nuwtld6tudy3"
    },
    {
      "id": "lt-pair-xapi-tracks",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "xAPI"
      },
      "sideB": {
        "modality": "text",
        "value": "Actor-Verb-Object statements; offline, simulations, on-the-job"
      },
      "tags": [
        "standards",
        "lms"
      ],
      "uid": "pcr2cr12mmgzd"
    },
    {
      "id": "lt-pair-lrs-role",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "LRS"
      },
      "sideB": {
        "modality": "text",
        "value": "Backend store for xAPI statements"
      },
      "tags": [
        "standards",
        "lms"
      ],
      "uid": "6759s44klktw"
    },
    {
      "id": "lt-mcq-canvas",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "Which LMS is noted for being instruction-friendly and gaining market share from Blackboard?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Canvas"
        },
        {
          "modality": "text",
          "value": "Moodle"
        },
        {
          "modality": "text",
          "value": "Brightspace"
        },
        {
          "modality": "text",
          "value": "Schoology"
        }
      ],
      "correctIndex": 0,
      "explanation": "Canvas is instruction-friendly and has been taking market share from Blackboard. Moodle is the open-source global leader; Brightspace is another current leader.",
      "tags": [
        "lms",
        "edtech"
      ],
      "uid": "1budzx81k1rjrg"
    },
    {
      "id": "lt-mcq-xapi-statement",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "xAPI records learning experiences in what statement form?"
      },
      "options": [
        {
          "modality": "text",
          "value": "User-Action-Score"
        },
        {
          "modality": "text",
          "value": "Learner-Activity-Result"
        },
        {
          "modality": "text",
          "value": "Actor-Verb-Object"
        },
        {
          "modality": "text",
          "value": "Source-Event-Timestamp"
        }
      ],
      "correctIndex": 2,
      "explanation": "xAPI uses 'Actor-Verb-Object' statements, e.g. 'Jane completed the quiz scoring 85%' — far richer than SCORM's completions and scores.",
      "tags": [
        "standards",
        "lms"
      ],
      "uid": "1jrlkxf8svdyx"
    },
    {
      "id": "lt-cmp-scorm-xapi",
      "shape": "comparison",
      "prompt": "You need to track a learner's performance during an offline field simulation, not just a finished quiz. Which standard fits?",
      "correct": {
        "caption": "xAPI: Actor-Verb-Object statements capture offline, simulation, and on-the-job activity",
        "imageSearchTerm": "learning analytics dashboard",
        "imagePrompt": "Clean modern dashboard UI showing a stream of learning-activity statements with actor, verb and object columns, charts of offline and simulation events, cool blue palette, flat illustration"
      },
      "incorrect": {
        "caption": "SCORM: only records course completions and simple quiz scores within the LMS itself",
        "imageSearchTerm": "checklist completed quiz score",
        "imagePrompt": "Minimal illustration of a simple course-completion checkmark and a single quiz percentage score on an LMS screen, limited data, muted grey palette, flat style"
      },
      "explanation": "SCORM (2001) tracks completions and quiz scores only. xAPI succeeds it by recording virtually any experience — offline, simulations, on-the-job — as Actor-Verb-Object statements stored in an LRS.",
      "tags": [
        "standards",
        "lms"
      ],
      "uid": "1wl4eny1mugb9u"
    },
    {
      "id": "lt-def-gamification",
      "shape": "definition",
      "term": {
        "modality": "text",
        "value": "Gamification"
      },
      "definition": {
        "modality": "text",
        "value": "The application of game design elements — points, badges, leaderboards, levels, narrative, challenges — to non-game contexts to increase engagement and motivation. Term coined by Nick Pelling in 2003."
      },
      "tags": [
        "gamification",
        "vocabulary"
      ],
      "uid": "3rpswusrv7qq"
    },
    {
      "id": "lt-fact-gamification-origins",
      "shape": "fact",
      "title": "Older than the buzzword",
      "body": "**Nick Pelling** coined *gamification* in 2003, but its educational roots are older: **Thomas Malone's** 1980 study on intrinsically motivating computer games asked what actually makes games engaging. **Jesse Schell**'s 2010 DICE talk predicted game elements would invade everyday life; **Jane McGonigal**'s *Reality Is Broken* (2011) argued we should harness gamer motivation for real-world problems.",
      "tags": [
        "gamification",
        "history"
      ],
      "studyGuideAnchor": "older-than-the-buzzword",
      "illustration": {
        "imageSearchTerm": "retro arcade video game",
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        "alt": "Older than the buzzword",
        "depictable": false,
        "credit": "Pexels · Close-up of retro arcade game controls with joystick and buttons",
        "creditUrl": "https://www.pexels.com/photo/vintage-arcade-game-controls-close-up-30512715/",
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      },
      "uid": "1ns4woq0si08"
    },
    {
      "id": "lt-pair-schell",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Jesse Schell"
      },
      "sideB": {
        "modality": "text",
        "value": "2010 DICE talk: game elements will invade everyday life"
      },
      "tags": [
        "gamification",
        "thinkers"
      ],
      "uid": "1wgxez1w1kdk7"
    },
    {
      "id": "lt-pair-mcgonigal",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Jane McGonigal"
      },
      "sideB": {
        "modality": "text",
        "value": "Reality Is Broken (2011)"
      },
      "tags": [
        "gamification",
        "thinkers"
      ],
      "uid": "1vprqtg15cbww4"
    },
    {
      "id": "lt-pair-kapp",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Karl Kapp"
      },
      "sideB": {
        "modality": "text",
        "value": "The Gamification of Learning and Instruction (2012)"
      },
      "tags": [
        "gamification",
        "thinkers"
      ],
      "uid": "1dku77xk1u287"
    },
    {
      "id": "lt-pair-salen-zimmerman",
      "shape": "pair",
      "sideA": {
        "modality": "text",
        "value": "Salen & Zimmerman"
      },
      "sideB": {
        "modality": "text",
        "value": "Rules of Play (2004)"
      },
      "tags": [
        "gamification",
        "thinkers"
      ],
      "uid": "1l8zvd1lvfjdj"
    },
    {
      "id": "lt-mcq-mechanics",
      "shape": "mcq",
      "prompt": {
        "modality": "text",
        "value": "Which core game mechanic reframes failure as information rather than judgment?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Mastery framing"
        },
        {
          "modality": "text",
          "value": "Narrative framing"
        },
        {
          "modality": "text",
          "value": "Scaffolded difficulty"
        },
        {
          "modality": "text",
          "value": "Social connection"
        }
      ],
      "correctIndex": 0,
      "explanation": "Mastery framing treats failure as feedback, not a verdict. Narrative framing supplies the fantasy Malone identified; scaffolded difficulty implements the ZPD; social connection drives leaderboards and co-op.",
      "tags": [
        "gamification",
        "mechanics"
      ],
      "uid": "z5c9d4cr5szc"
    },
    {
      "id": "lt-cmp-intrinsic-extrinsic",
      "shape": "comparison",
      "prompt": "Which approach is the safer foundation for a learning app that wants durable engagement?",
      "correct": {
        "caption": "Intrinsic: social reinforcement and progress visualization that support autonomy and competence",
        "imageSearchTerm": "person enjoying learning",
        "imagePrompt": "Warm illustration of a learner absorbed and satisfied while studying, a subtle progress bar filling, friends cheering, cozy palette, conveying intrinsic enjoyment and momentum, flat style"
      },
      "incorrect": {
        "caption": "Purely extrinsic: badges, points, and streaks as ends in themselves, crowding out learning",
        "imageSearchTerm": "trophy badges points",
        "imagePrompt": "Illustration of a pile of badges, points and a streak counter dominating a screen while the actual lesson is tiny and ignored, slightly cold transactional feel, flat style"
      },
      "explanation": "Deci (1971) and Kohn's Punished by Rewards (1993) warn that transactional rewards crowd out learning motivation. Well-designed systems like Duolingo's lean on social reinforcement and progress visualization instead.",
      "tags": [
        "gamification",
        "motivation"
      ],
      "uid": "ldl1srxhosdd"
    },
    {
      "id": "lt-concept-skinner",
      "shape": "concept",
      "conceptKind": "person",
      "tags": [
        "key-concept",
        "person",
        "theorist"
      ],
      "name": "B.F. Skinner",
      "clues": [
        "An early-20th-century American psychologist and the most influential figure in behaviorism.",
        "He studied how rewards and punishments shape voluntary behavior, coining the term 'operant conditioning.'",
        "He invented programmed-instruction 'teaching machines' and the chamber used to study reinforcement schedules."
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "illustration": {
        "imagePrompt": "Black-and-white portrait photograph of psychologist B.F. Skinner",
        "imageSearchTerm": "B.F. Skinner portrait",
        "alt": "Portrait of psychologist B.F. Skinner",
        "credit": "Pexels · Close-up portrait of a bearded senior man with eyeglasses indoors.",
        "creditUrl": "https://www.pexels.com/photo/man-in-black-crew-neck-shirt-wearing-black-framed-eyeglasses-3642644/",
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      },
      "uid": "m445mz1qjka35"
    },
    {
      "id": "lt-concept-pavlov",
      "shape": "concept",
      "conceptKind": "person",
      "tags": [
        "key-concept",
        "person",
        "theorist"
      ],
      "name": "Ivan Pavlov",
      "clues": [
        "A Russian physiologist whose work on the digestive system earned a Nobel Prize.",
        "He found that a neutral stimulus, repeatedly paired with food, could itself trigger a reflex.",
        "His experiments conditioning dogs to salivate at a bell became the classic demonstration of classical conditioning."
      ],
      "source": {
        "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
      },
      "illustration": {
        "imagePrompt": "Black-and-white portrait photograph of physiologist Ivan Pavlov with a long beard",
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        "A learning theory proposed around 2004–05 explicitly 'for the digital age.'",
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        "Knowing where to find current information matters more than what you currently know."
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        "An evidence-based study method that decisively beats cramming for long-term retention.",
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        "Software like Anki and SuperMemo schedules each review near the moment of forgetting."
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        "A robust cognitive-psychology finding about how studying actually works.",
        "Actively retrieving information from memory strengthens it far more than re-reading does.",
        "It is why frequent low-stakes quizzes beat passive review — also called retrieval practice."
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          "value": "A review adds the most once the material has decayed to a stable floor",
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          "value": "Transferring a learned response to new stimuli that resemble the original",
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          "value": "Pairing a neutral stimulus with a reward until it alone triggers the response",
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        "value": "In Piaget's account, why is mildly surprising information often remembered better than information that merely confirms what you already know?"
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        {
          "modality": "text",
          "value": "It fits an existing schema, and the ease of assimilating it into place leaves a stronger memory trace",
          "short": "Fits a schema; assimilated easily"
        },
        {
          "modality": "text",
          "value": "It contradicts an existing schema, and the drive to resolve that disequilibrium forces effortful accommodation",
          "short": "Disequilibrium forces accommodation"
        },
        {
          "modality": "text",
          "value": "It overloads working memory's limited slots, and the strain of rehearsing it etches the material in deeper",
          "short": "Overloads working memory; etched deeper"
        },
        {
          "modality": "text",
          "value": "It compresses into a single meaningful chunk, and the freed working-memory slots make it easier to recall",
          "short": "Chunked into one unit; easier recall"
        }
      ],
      "correctIndex": 1,
      "explanation": "A clash between an old schema and new experience creates disequilibrium; equilibration, the drive to resolve it, produces effortful accommodation and a stronger memory.",
      "uid": "nek9c41bnb11o"
    },
    {
      "id": "mcq-rw-l4-p4-cognitive-load",
      "shape": "mcq",
      "tags": [
        "cognitive-load",
        "instructional-design"
      ],
      "prompt": {
        "modality": "text",
        "value": "In Cognitive Load Theory, which type of load should instructional designers try to MAXIMIZE?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Germane load"
        },
        {
          "modality": "text",
          "value": "Intrinsic load"
        },
        {
          "modality": "text",
          "value": "Extraneous load"
        }
      ],
      "correctIndex": 0,
      "explanation": "Germane load is the productive effort spent building mental schemas, so designers should maximize it. Extraneous load comes from poor design and should be minimized; intrinsic load is fixed by the topic's inherent complexity.",
      "uid": "106rkam1q5lf9m"
    },
    {
      "id": "mcq-rw-l5-p1-addie",
      "shape": "mcq",
      "tags": [
        "addie",
        "instructional-design",
        "evaluation"
      ],
      "prompt": {
        "modality": "text",
        "value": "How does the Evaluate phase function in the ADDIE model?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It is a single final gate performed only after the course is delivered",
          "short": "A single final gate after delivery"
        },
        {
          "modality": "text",
          "value": "It threads through all five phases, surfacing problems early rather than only at the end",
          "short": "Threads through all five phases"
        },
        {
          "modality": "text",
          "value": "It is optional and usually skipped for high-stakes compliance training",
          "short": "Optional; skipped for compliance"
        },
        {
          "modality": "text",
          "value": "It replaces the Analyze phase in modern iterative versions",
          "short": "It replaces the Analyze phase"
        }
      ],
      "correctIndex": 1,
      "explanation": "ADDIE's Evaluate is not a final gate — it runs continuously through Analyze, Design, Develop, and Implement, catching design flaws early instead of waiting until after delivery.",
      "uid": "1pughho16z2c3w"
    },
    {
      "id": "mcq-rw-l6-p2-khanmigo-debate",
      "shape": "mcq",
      "tags": [
        "khanmigo",
        "critique",
        "edtech-debate"
      ],
      "prompt": {
        "modality": "text",
        "value": "In his contrarian review, critic John Warner argues that Brave New Words is flawed because it..."
      },
      "options": [
        {
          "modality": "text",
          "value": "urges educators to wait out the risks instead of adopting tools carefully",
          "short": "Urges waiting out the risks"
        },
        {
          "modality": "text",
          "value": "treats hallucination, bias, and privacy as risks already engineered away",
          "short": "Treats the risks as engineered away"
        },
        {
          "modality": "text",
          "value": "narrows the case for AI tutoring to schoolchildren and their classrooms",
          "short": "Narrows the case to schoolchildren"
        },
        {
          "modality": "text",
          "value": "substitutes technology optimism for rigorous pedagogical evidence",
          "short": "Swaps evidence for tech optimism"
        }
      ],
      "correctIndex": 3,
      "explanation": "Warner charges that Khan assumes transformation will happen because the tools are impressive, not because controlled research shows learning gains. The other options describe positions the book actually takes the opposite of.",
      "uid": "1vx4qepn2fi6r"
    },
    {
      "id": "mcq-rw-l7-p4-market",
      "shape": "mcq",
      "tags": [
        "edtech-market",
        "investment",
        "workforce-training"
      ],
      "prompt": {
        "modality": "text",
        "value": "By deal volume, which segment captured the largest share of 2025 EdTech investment?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Early childhood"
        },
        {
          "modality": "text",
          "value": "Post-secondary"
        },
        {
          "modality": "text",
          "value": "K-12 education"
        },
        {
          "modality": "text",
          "value": "Workforce training"
        }
      ],
      "correctIndex": 3,
      "explanation": "2025 EdTech deal volume split workforce training 38%, K-12 36%, post-secondary 22%, and early childhood 4%. Workforce narrowly led — mirrored by the year's two biggest deals, Workday–Sana and Coursera–Udemy.",
      "uid": "1e0dqrlkug0j7"
    },
    {
      "id": "mcq-rw-l9-p1-theorists",
      "shape": "mcq",
      "tags": [
        "bloom",
        "tutoring",
        "theorists"
      ],
      "prompt": {
        "modality": "text",
        "value": "Benjamin Bloom's famous 1984 finding claimed that one-to-one tutoring lifts the average student's performance by how much, versus conventional classroom instruction?"
      },
      "options": [
        {
          "modality": "text",
          "value": "One standard deviation"
        },
        {
          "modality": "text",
          "value": "Three standard deviations"
        },
        {
          "modality": "text",
          "value": "Half a standard deviation"
        },
        {
          "modality": "text",
          "value": "Two standard deviations"
        }
      ],
      "correctIndex": 3,
      "explanation": "Bloom's 1984 result — the '2 sigma problem' — found one-to-one tutoring raised average students two standard deviations above classroom peers. It's the benchmark adaptive and AI tutoring try to reach at scale.",
      "uid": "1cn869x1mn2bw7"
    },
    {
      "id": "mcq-rw-l9-p2-frameworks",
      "shape": "mcq",
      "tags": [
        "addie",
        "instructional-design",
        "frameworks"
      ],
      "prompt": {
        "modality": "text",
        "value": "The ADDIE model, the dominant framework for building a course, stands for which sequence of five stages?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Analyze, Draft, Deliver, Integrate, Examine"
        },
        {
          "modality": "text",
          "value": "Assess, Design, Deploy, Instruct, Evaluate"
        },
        {
          "modality": "text",
          "value": "Analyze, Design, Develop, Implement, Evaluate"
        },
        {
          "modality": "text",
          "value": "Assemble, Design, Demonstrate, Improve, Extend"
        }
      ],
      "correctIndex": 2,
      "explanation": "ADDIE = Analyze, Design, Develop, Implement, Evaluate — the dominant instructional-design framework, taking a course from needs analysis through build-out to a final evaluation.",
      "uid": "1yzbogo1q93ni8"
    },
    {
      "id": "mcq-rw-l9-p3-right-or-wrong",
      "shape": "mcq",
      "tags": [
        "testing-effect",
        "retrieval-practice",
        "active-learning"
      ],
      "prompt": {
        "modality": "text",
        "value": "According to the Testing Effect (retrieval practice), which study strategy builds the most durable long-term memory?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Retrieving information from memory, e.g. self-quizzing"
        },
        {
          "modality": "text",
          "value": "Listening to the lecture again"
        },
        {
          "modality": "text",
          "value": "Highlighting the key passages"
        },
        {
          "modality": "text",
          "value": "Re-reading the material several times"
        }
      ],
      "correctIndex": 0,
      "explanation": "The Testing Effect shows that pulling information *out* of memory — self-quizzing — beats putting it back *in* by re-reading or highlighting. Retrieval is the more effortful, and more durable, practice.",
      "uid": "1kmqwdgwf2u3g"
    },
    {
      "id": "mcq-rw-l10-p1-ai-adaptive",
      "shape": "mcq",
      "tags": [
        "cognitive-tutor",
        "intelligent-tutoring",
        "adaptive-systems"
      ],
      "prompt": {
        "modality": "text",
        "value": "The Cognitive Tutor, the canonical Intelligent Tutoring System, was developed at which university and originally for which subject?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Harvard, originally reading comprehension"
        },
        {
          "modality": "text",
          "value": "Stanford, originally computer science"
        },
        {
          "modality": "text",
          "value": "Carnegie Mellon, originally mathematics"
        },
        {
          "modality": "text",
          "value": "MIT, originally introductory physics"
        }
      ],
      "correctIndex": 2,
      "explanation": "The Cognitive Tutor was built at Carnegie Mellon. It models student cognition and delivers personalized hints and feedback within one domain — originally mathematics — making it the textbook example of an ITS.",
      "uid": "1k49p4g1r41cp4"
    },
    {
      "id": "mcq-rw-l10-p1b-ai-infrastructure",
      "shape": "mcq",
      "tags": [
        "agentic-ai",
        "generative-ai",
        "ai-infrastructure"
      ],
      "prompt": {
        "modality": "text",
        "value": "What most distinguishes Agentic AI from ordinary Generative AI in an edtech pipeline?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It can route every output through a human reviewer, who approves or overrides it before delivery",
          "short": "Routes every output through a human"
        },
        {
          "modality": "text",
          "value": "It can produce novel text, images, or audio from a single prompt, generating content and feedback at scale",
          "short": "Generates content from one prompt"
        },
        {
          "modality": "text",
          "value": "It can autonomously plan, use tools, and pursue multi-step goals with minimal human intervention",
          "short": "Autonomously plans and uses tools"
        },
        {
          "modality": "text",
          "value": "It can detect a learner's frustration, boredom, or curiosity and adapt the next instruction to match",
          "short": "Detects and adapts to learner emotion"
        }
      ],
      "correctIndex": 2,
      "explanation": "Generative AI produces content; Agentic AI goes further, autonomously planning, using tools, and pursuing multi-step goals — able to orchestrate curriculum planning, content generation, assessment, and feedback in a single loop.",
      "uid": "mcadw5dvey6v"
    },
    {
      "id": "mcq-rw-l10-p2-pedagogy",
      "shape": "mcq",
      "tags": [
        "microlearning",
        "pedagogy",
        "instruction"
      ],
      "prompt": {
        "modality": "text",
        "value": "Microlearning delivers content in bursts of what length, and each burst is built around how many learning objectives?"
      },
      "options": [
        {
          "modality": "text",
          "value": "20–30 minutes, built around several learning objectives"
        },
        {
          "modality": "text",
          "value": "2–10 minutes, built around a single learning objective"
        },
        {
          "modality": "text",
          "value": "30–60 seconds, built around a single learning objective"
        },
        {
          "modality": "text",
          "value": "45–60 minutes, built around one unit's learning objectives"
        }
      ],
      "correctIndex": 1,
      "explanation": "Microlearning delivers content in short, focused bursts of two to ten minutes, each built around a single learning objective — a format well suited to mobile usage and limited attention spans.",
      "uid": "1cynu4j1d4yykp"
    },
    {
      "id": "mcq-rw-l10-p2b-learning-science",
      "shape": "mcq",
      "tags": [
        "self-determination-theory",
        "motivation",
        "learning-science"
      ],
      "prompt": {
        "modality": "text",
        "value": "Self-Determination Theory names which three basic psychological needs that drive intrinsic motivation?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Challenge, fantasy, and curiosity"
        },
        {
          "modality": "text",
          "value": "Autonomy, competence, and relatedness"
        },
        {
          "modality": "text",
          "value": "Attention, retention, and reproduction"
        },
        {
          "modality": "text",
          "value": "Context, culture, and collaboration"
        }
      ],
      "correctIndex": 1,
      "explanation": "Deci & Ryan's Self-Determination Theory (1985) names autonomy, competence, and relatedness as the three needs behind intrinsic motivation — the framework cited most often in gamification and engagement design.",
      "uid": "12jzj0u1km0ii2"
    },
    {
      "id": "mcq-rw-l10-p3-assessment-data",
      "shape": "mcq",
      "tags": [
        "kirkpatrick",
        "training-evaluation",
        "assessment"
      ],
      "prompt": {
        "modality": "text",
        "value": "In the Kirkpatrick Model of training evaluation, which of the four levels asks whether learners actually applied what they learned back on the job?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Learning"
        },
        {
          "modality": "text",
          "value": "Results"
        },
        {
          "modality": "text",
          "value": "Behavior"
        },
        {
          "modality": "text",
          "value": "Reaction"
        }
      ],
      "correctIndex": 2,
      "explanation": "Kirkpatrick's four levels run Reaction (did they like it?), Learning (did they gain knowledge?), Behavior (did they apply it on the job?), and Results (did it affect outcomes?). Behavior is the application level.",
      "uid": "1uvm8eiysdksu"
    },
    {
      "id": "czr-learning-theory-lt-def-hebbian",
      "shape": "cloze",
      "tags": [
        "learning-science",
        "neuroscience"
      ],
      "template": "___ — The principle that synaptic connections between neurons strengthen when they activate together — 'neurons that fire together, wire together.'",
      "answer": "Hebbian learning",
      "distractors": [
        "Autotelic activity",
        "Intrinsic load",
        "Germane load"
      ],
      "derivedFrom": "lt-def-hebbian",
      "explanation": "Compare: Autotelic activity — An activity that is intrinsically rewarding — done for its own sake, not for an external payoff. The eighth hallmark of flow. Intrinsic load — The cognitive load that comes from the inherent complexity of the material itself — unavoidable, and set by the topic.",
      "uid": "18cag401xgmgk8"
    },
    {
      "id": "czr-learning-theory-lt-def-forgetting-curve",
      "shape": "cloze",
      "tags": [
        "memory",
        "forgetting-curve"
      ],
      "template": "___ — Ebbinghaus's finding that memory of new information decays exponentially over time without review, losing most of it within a day",
      "answer": "Forgetting curve",
      "distractors": [
        "Hermann Ebbinghaus",
        "Keyword Method",
        "Spaced repetition"
      ],
      "derivedFrom": "lt-def-forgetting-curve",
      "explanation": "Compare: Hermann Ebbinghaus — A 19th-century German psychologist who pioneered the experimental study of memory. Keyword Method — A language-learning mnemonic that links a foreign word's sound to a memorable image which bridges to the translation.",
      "uid": "inbia5xjdp0n"
    },
    {
      "id": "czr-learning-theory-lt-def-spaced-repetition",
      "shape": "cloze",
      "tags": [
        "memory",
        "spaced-repetition"
      ],
      "template": "___ — Distributing study sessions over expanding intervals, which produces far better retention than the same time spent cramming in one sitting",
      "answer": "Spaced repetition",
      "distractors": [
        "SRS apps that schedule reviews at the optimal interval",
        "SRS (Spaced Repetition Software)",
        "Forgetting curve"
      ],
      "derivedFrom": "lt-def-spaced-repetition",
      "explanation": "Compare: SRS apps that schedule reviews at the optimal interval — Anki / SuperMemo. SRS (Spaced Repetition Software) — Software like Anki and SuperMemo that algorithmically schedules each review at the moment of maximum forgetting — the optimal interval.",
      "uid": "2e7m4mraqno2"
    },
    {
      "id": "czr-learning-theory-lt-def-srs",
      "shape": "cloze",
      "tags": [
        "memory",
        "spaced-repetition",
        "edtech"
      ],
      "template": "___ — Software like Anki and SuperMemo that algorithmically schedules each review at the moment of maximum forgetting — the optimal interval",
      "answer": "SRS (Spaced Repetition Software)",
      "distractors": [
        "Method of Loci (Memory Palace)",
        "Keyword Method",
        "Dual Coding Theory"
      ],
      "derivedFrom": "lt-def-srs",
      "explanation": "Compare: Method of Loci (Memory Palace) — An ancient technique that places items to be memorized at spatial locations along a familiar mental journey; walking the path retrieves them in sequence.",
      "uid": "jjl77p15z8k4n"
    },
    {
      "id": "czr-learning-theory-lt-def-retrieval-practice",
      "shape": "cloze",
      "tags": [
        "retrieval",
        "testing-effect"
      ],
      "template": "___ — Strengthening memory by actively recalling information rather than re-exposing yourself to it; the mechanism behind the testing effect",
      "answer": "Retrieval practice",
      "distractors": [
        "Spaced repetition",
        "Dual Coding Theory",
        "Interleaving"
      ],
      "derivedFrom": "lt-def-retrieval-practice",
      "explanation": "Compare: Spaced repetition — Distributing study sessions over expanding intervals, which produces far better retention than the same time spent cramming in one sitting.",
      "uid": "du8wrb15xuwrp"
    },
    {
      "id": "czr-learning-theory-lt-def-als",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — Software that dynamically adjusts content difficulty, sequence, and modality based on ongoing learner performance data",
      "answer": "Adaptive Learning System (ALS)",
      "distractors": [
        "Bayesian Knowledge Tracing (BKT)",
        "Human-in-the-Loop (HITL)",
        "Generative AI (GenAI)"
      ],
      "derivedFrom": "lt-def-als",
      "explanation": "Compare: Bayesian Knowledge Tracing (BKT) — A probabilistic model used in intelligent tutoring systems to estimate the probability that a learner has mastered a skill, updating that estimate after each response.",
      "uid": "h3vw42dwld66"
    },
    {
      "id": "czr-learning-theory-lt-def-agentic-ai",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — Autonomous AI that can plan, take actions, use tools, and pursue goals across multiple steps with minimal human intervention. In education it can orchestrate curriculum planning, content generation, assessment, and feedback in one loop",
      "answer": "Agentic AI",
      "distractors": [
        "Prompt Engineering",
        "Ontology (Learning)",
        "Affective Computing"
      ],
      "derivedFrom": "lt-def-agentic-ai",
      "explanation": "Compare: Prompt Engineering — Designing the inputs given to LLMs so they produce the desired instructional outputs — a practical skill for edtech builders working with foundation models.",
      "uid": "1wesmj1v40enb"
    },
    {
      "id": "czr-learning-theory-lt-def-generative-ai",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — AI systems that produce novel text, images, or audio. In education, GenAI enables dynamic content creation, conversational tutoring, and personalized feedback at scale",
      "answer": "Generative AI (GenAI)",
      "distractors": [
        "Zero-Shot Learning (AI)",
        "Algorithm-Based Sequencing",
        "Curriculum Graph / Knowledge Graph"
      ],
      "derivedFrom": "lt-def-generative-ai",
      "explanation": "Compare: Zero-Shot Learning (AI) — An LLM's ability to perform a task it was not explicitly trained on, generalizing from broad pre-training — relevant to generating curriculum for rare or niche subjects.",
      "uid": "106jpj11kn47tj"
    },
    {
      "id": "czr-learning-theory-lt-def-bkt",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — A probabilistic model used in intelligent tutoring systems to estimate the probability that a learner has mastered a skill, updating that estimate after each response",
      "answer": "Bayesian Knowledge Tracing (BKT)",
      "distractors": [
        "Zero-Shot Learning (AI)",
        "Human-in-the-Loop (HITL)",
        "Intelligent Tutoring System (ITS)"
      ],
      "derivedFrom": "lt-def-bkt",
      "explanation": "Compare: Zero-Shot Learning (AI) — An LLM's ability to perform a task it was not explicitly trained on, generalizing from broad pre-training — relevant to generating curriculum for rare or niche subjects.",
      "uid": "1pijbmkjh49v0"
    },
    {
      "id": "czr-learning-theory-lt-def-dkt",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — A recurrent neural network (LSTM) approach to knowledge tracing that models learner knowledge as a hidden state evolving with each interaction (Piech et al., 2015)",
      "answer": "Deep Knowledge Tracing (DKT)",
      "distractors": [
        "Zero-Shot Learning (AI)",
        "Algorithm-Based Sequencing",
        "Bayesian Knowledge Tracing (BKT)"
      ],
      "derivedFrom": "lt-def-dkt",
      "explanation": "Compare: Zero-Shot Learning (AI) — An LLM's ability to perform a task it was not explicitly trained on, generalizing from broad pre-training — relevant to generating curriculum for rare or niche subjects.",
      "uid": "1x2y9n71dpn5t"
    },
    {
      "id": "czr-learning-theory-lt-def-knowledge-state",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — A model representing what a specific learner currently knows and doesn't know within a domain, updated continuously by the system",
      "answer": "Knowledge State",
      "distractors": [
        "Ontology (Learning)",
        "Affective Computing",
        "Prompt Engineering"
      ],
      "derivedFrom": "lt-def-knowledge-state",
      "explanation": "Compare: Ontology (Learning) — A formal representation of knowledge and the relationships between concepts in a domain, used to structure curriculum graphs and content recommendations.",
      "uid": "c6w20b16m6kox"
    },
    {
      "id": "czr-learning-theory-lt-def-its",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — Software that provides personalized instruction and feedback without a human teacher in the loop, using models of the domain, the learner, and pedagogy",
      "answer": "Intelligent Tutoring System (ITS)",
      "distractors": [
        "Zero-Shot Learning (AI)",
        "Bayesian Knowledge Tracing (BKT)",
        "Generative AI (GenAI)"
      ],
      "derivedFrom": "lt-def-its",
      "explanation": "Compare: Zero-Shot Learning (AI) — An LLM's ability to perform a task it was not explicitly trained on, generalizing from broad pre-training — relevant to generating curriculum for rare or niche subjects.",
      "uid": "yhsbo2tqmhc6"
    },
    {
      "id": "czr-learning-theory-lt-def-cognitive-tutor",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — An AI tutoring system developed at Carnegie Mellon that models student cognition and gives personalized hints and feedback within a specific domain, originally mathematics",
      "answer": "Cognitive Tutor",
      "distractors": [
        "Affective Computing",
        "Agentic AI",
        "Ontology (Learning)"
      ],
      "derivedFrom": "lt-def-cognitive-tutor",
      "explanation": "Compare: Affective Computing — AI systems that detect and respond to learner emotions — frustration, boredom, curiosity — to adapt instruction accordingly.",
      "uid": "jkug47ox904l"
    },
    {
      "id": "czr-learning-theory-lt-def-algorithm-sequencing",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — Using ML models (often BKT or DKT) to predict learner knowledge states and determine the optimal next item to present",
      "answer": "Algorithm-Based Sequencing",
      "distractors": [
        "Human-in-the-Loop (HITL)",
        "Bayesian Knowledge Tracing (BKT)",
        "Generative AI (GenAI)"
      ],
      "derivedFrom": "lt-def-algorithm-sequencing",
      "explanation": "Compare: Human-in-the-Loop (HITL) — AI system design where humans review, approve, or override AI outputs before delivery — used in responsible edtech to catch errors and ensure quality.",
      "uid": "4b3eo64yseve"
    },
    {
      "id": "czr-learning-theory-lt-def-zero-shot",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — An LLM's ability to perform a task it was not explicitly trained on, generalizing from broad pre-training — relevant to generating curriculum for rare or niche subjects",
      "answer": "Zero-Shot Learning (AI)",
      "distractors": [
        "Human-in-the-Loop (HITL)",
        "Adaptive Learning System (ALS)",
        "Generative AI (GenAI)"
      ],
      "derivedFrom": "lt-def-zero-shot",
      "explanation": "Compare: Human-in-the-Loop (HITL) — AI system design where humans review, approve, or override AI outputs before delivery — used in responsible edtech to catch errors and ensure quality.",
      "uid": "z6hv8w7nyghk"
    },
    {
      "id": "czr-learning-theory-lt-def-affective-computing",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — AI systems that detect and respond to learner emotions — frustration, boredom, curiosity — to adapt instruction accordingly",
      "answer": "Affective Computing",
      "distractors": [
        "Cognitive Tutor",
        "Prompt Engineering",
        "Knowledge State"
      ],
      "derivedFrom": "lt-def-affective-computing",
      "explanation": "Compare: Cognitive Tutor — An AI tutoring system developed at Carnegie Mellon that models student cognition and gives personalized hints and feedback within a specific domain, originally mathematics.",
      "uid": "1kvib9b1yu0czx"
    },
    {
      "id": "czr-learning-theory-lt-def-knowledge-graph",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — A structured representation of learning objectives and their dependencies, used by adaptive systems to find prerequisite relationships and optimal learning paths",
      "answer": "Curriculum Graph / Knowledge Graph",
      "distractors": [
        "Bayesian Knowledge Tracing (BKT)",
        "Algorithm-Based Sequencing",
        "Human-in-the-Loop (HITL)"
      ],
      "derivedFrom": "lt-def-knowledge-graph",
      "explanation": "Compare: Bayesian Knowledge Tracing (BKT) — A probabilistic model used in intelligent tutoring systems to estimate the probability that a learner has mastered a skill, updating that estimate after each response.",
      "uid": "u2lj8s13q5u7o"
    },
    {
      "id": "czr-learning-theory-lt-def-ontology",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — A formal representation of knowledge and the relationships between concepts in a domain, used to structure curriculum graphs and content recommendations",
      "answer": "Ontology (Learning)",
      "distractors": [
        "Cognitive Tutor",
        "Agentic AI",
        "Affective Computing"
      ],
      "derivedFrom": "lt-def-ontology",
      "explanation": "Compare: Cognitive Tutor — An AI tutoring system developed at Carnegie Mellon that models student cognition and gives personalized hints and feedback within a specific domain, originally mathematics.",
      "uid": "3zglyfl3puhp"
    },
    {
      "id": "czr-learning-theory-lt-def-prompt-engineering",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — Designing the inputs given to LLMs so they produce the desired instructional outputs — a practical skill for edtech builders working with foundation models",
      "answer": "Prompt Engineering",
      "distractors": [
        "Knowledge State",
        "Cognitive Tutor",
        "Ontology (Learning)"
      ],
      "derivedFrom": "lt-def-prompt-engineering",
      "explanation": "Compare: Knowledge State — A model representing what a specific learner currently knows and doesn't know within a domain, updated continuously by the system.",
      "uid": "xjqhfq1vzvb0q"
    },
    {
      "id": "czr-learning-theory-lt-def-hitl",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "template": "___ — AI system design where humans review, approve, or override AI outputs before delivery — used in responsible edtech to catch errors and ensure quality",
      "answer": "Human-in-the-Loop (HITL)",
      "distractors": [
        "Algorithm-Based Sequencing",
        "Deep Knowledge Tracing (DKT)",
        "Bayesian Knowledge Tracing (BKT)"
      ],
      "derivedFrom": "lt-def-hitl",
      "explanation": "Compare: Algorithm-Based Sequencing — Using ML models (often BKT or DKT) to predict learner knowledge states and determine the optimal next item to present.",
      "uid": "rslx1pn6jorz"
    },
    {
      "id": "czr-learning-theory-lt-def-metacognition",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "template": "___ — Thinking about one's own thinking — awareness of one's learning process, knowledge gaps, and strategies. Tutors like Khanmigo foster it by asking students to explain their reasoning",
      "answer": "Metacognition",
      "distractors": [
        "Transfer of Learning",
        "Working Memory",
        "Microlearning"
      ],
      "derivedFrom": "lt-def-metacognition",
      "explanation": "Compare: Transfer of Learning — Applying knowledge or skills learned in one context to new, different contexts. It is the ultimate goal of deep learning; shallow memorization often fails to transfer.",
      "uid": "14s145avyflqq"
    },
    {
      "id": "czr-learning-theory-lt-def-differentiated-instruction",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "template": "___ — Tailoring content, process, or product to individual learner needs within a classroom setting — the human precursor to algorithmic personalization",
      "answer": "Differentiated Instruction",
      "distractors": [
        "Scaffolded Curriculum",
        "Pedagogical Content Knowledge (PCK)",
        "Personalized Learning"
      ],
      "derivedFrom": "lt-def-differentiated-instruction",
      "explanation": "Compare: Scaffolded Curriculum — A structured learning sequence that provides appropriate support at each level and fades assistance as competence grows — directly implementing Vygotsky's ZPD.",
      "uid": "o1443b1q78dl1"
    },
    {
      "id": "czr-learning-theory-lt-def-personalized-learning",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "template": "___ — An instructional approach that tailors pace, content, sequence, and modality to the individual learner's needs, goals, and learning style",
      "answer": "Personalized Learning",
      "distractors": [
        "Differentiated Instruction",
        "Pedagogical Content Knowledge (PCK)",
        "Scaffolded Curriculum"
      ],
      "derivedFrom": "lt-def-personalized-learning",
      "explanation": "Compare: Differentiated Instruction — Tailoring content, process, or product to individual learner needs within a classroom setting — the human precursor to algorithmic personalization.",
      "uid": "17whpp7y5lr7t"
    },
    {
      "id": "czr-learning-theory-lt-def-microlearning",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "template": "___ — Delivering content in short, focused bursts of 2–10 minutes, each built for a single learning objective. It exploits attention spans and mobile usage patterns",
      "answer": "Microlearning",
      "distractors": [
        "Transfer of Learning",
        "Multimodal Learning",
        "Metacognition"
      ],
      "derivedFrom": "lt-def-microlearning",
      "explanation": "Compare: Transfer of Learning — Applying knowledge or skills learned in one context to new, different contexts. It is the ultimate goal of deep learning; shallow memorization often fails to transfer.",
      "uid": "ixhl7wy13gpw"
    },
    {
      "id": "czr-learning-theory-lt-def-multimodal-learning",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "template": "___ — Engaging multiple sensory channels — visual, auditory, kinesthetic — together to deepen encoding. Grounded in dual coding and cognitive load theories",
      "answer": "Multimodal Learning",
      "distractors": [
        "Metacognition",
        "Chunking",
        "Microlearning"
      ],
      "derivedFrom": "lt-def-multimodal-learning",
      "explanation": "Compare: Metacognition — Thinking about one's own thinking — awareness of one's learning process, knowledge gaps, and strategies. Tutors like Khanmigo foster it by asking students to explain their reasoning.",
      "uid": "1h06m895a89k3"
    },
    {
      "id": "czr-learning-theory-lt-def-pbl",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "template": "___ — An approach where students learn by investigating and solving an authentic, complex, open-ended problem — rooted in Dewey's experiential philosophy",
      "answer": "Problem-Based Learning (PBL)",
      "distractors": [
        "Differentiated Instruction",
        "Pedagogical Content Knowledge (PCK)",
        "Competency-Based Education (CBE)"
      ],
      "derivedFrom": "lt-def-pbl",
      "explanation": "Compare: Differentiated Instruction — Tailoring content, process, or product to individual learner needs within a classroom setting — the human precursor to algorithmic personalization.",
      "uid": "1k5msv11enq73"
    },
    {
      "id": "czr-learning-theory-lt-def-scaffolded-curriculum",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "template": "___ — A structured learning sequence that provides appropriate support at each level and fades assistance as competence grows — directly implementing Vygotsky's ZPD",
      "answer": "Scaffolded Curriculum",
      "distractors": [
        "Differentiated Instruction",
        "Competency-Based Education (CBE)",
        "Pedagogical Content Knowledge (PCK)"
      ],
      "derivedFrom": "lt-def-scaffolded-curriculum",
      "explanation": "Compare: Differentiated Instruction — Tailoring content, process, or product to individual learner needs within a classroom setting — the human precursor to algorithmic personalization.",
      "uid": "f4qpgubu2mkq"
    },
    {
      "id": "czr-learning-theory-lt-def-cbe",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "template": "___ — An educational model where progression depends on demonstrating mastery of specific competencies, not on time spent in instruction",
      "answer": "Competency-Based Education (CBE)",
      "distractors": [
        "Problem-Based Learning (PBL)",
        "Personalized Learning",
        "Scaffolded Curriculum"
      ],
      "derivedFrom": "lt-def-cbe",
      "explanation": "Compare: Problem-Based Learning (PBL) — An approach where students learn by investigating and solving an authentic, complex, open-ended problem — rooted in Dewey's experiential philosophy.",
      "uid": "15qqehjwau7ot"
    },
    {
      "id": "czr-learning-theory-lt-def-pck",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "template": "___ — Shulman's 1986 concept: the specific knowledge teachers need about how to teach a particular subject, distinct from knowing the subject matter itself",
      "answer": "Pedagogical Content Knowledge (PCK)",
      "distractors": [
        "Scaffolded Curriculum",
        "Personalized Learning",
        "Competency-Based Education (CBE)"
      ],
      "derivedFrom": "lt-def-pck",
      "explanation": "Compare: Scaffolded Curriculum — A structured learning sequence that provides appropriate support at each level and fades assistance as competence grows — directly implementing Vygotsky's ZPD.",
      "uid": "p41ydh10838mn"
    },
    {
      "id": "czr-learning-theory-lt-def-transfer",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "template": "___ — Applying knowledge or skills learned in one context to new, different contexts. It is the ultimate goal of deep learning; shallow memorization often fails to transfer",
      "answer": "Transfer of Learning",
      "distractors": [
        "Multimodal Learning",
        "Working Memory",
        "Chunking"
      ],
      "derivedFrom": "lt-def-transfer",
      "explanation": "Compare: Multimodal Learning — Engaging multiple sensory channels — visual, auditory, kinesthetic — together to deepen encoding. Grounded in dual coding and cognitive load theories.",
      "uid": "twtzw9fqk07n"
    },
    {
      "id": "czr-learning-theory-lt-def-working-memory",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "template": "___ — The cognitive system that temporarily holds and manipulates information during active processing (about 7±2 items). Cognitive load theory focuses on its limits",
      "answer": "Working Memory",
      "distractors": [
        "Chunking",
        "Transfer of Learning",
        "Multimodal Learning"
      ],
      "derivedFrom": "lt-def-working-memory",
      "explanation": "Compare: Chunking — Breaking complex information into smaller, more manageable units to reduce cognitive load and improve encoding.",
      "uid": "oxta2xmjgbw3"
    },
    {
      "id": "czr-learning-theory-lt-def-chunking",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "template": "___ — Breaking complex information into smaller, more manageable units to reduce cognitive load and improve encoding",
      "answer": "Chunking",
      "distractors": [
        "Working Memory",
        "Microlearning",
        "Multimodal Learning"
      ],
      "derivedFrom": "lt-def-chunking",
      "explanation": "Compare: Working Memory — The cognitive system that temporarily holds and manipulates information during active processing (about 7±2 items). Cognitive load theory focuses on its limits.",
      "uid": "1xemav0rg75xg"
    },
    {
      "id": "czr-learning-theory-lt-def-formative-assessment",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "template": "___ — Assessment during the learning process to provide feedback and adjust instruction. Low-stakes quizzes that trigger retrieval practice are an example",
      "answer": "Formative Assessment",
      "distractors": [
        "Kirkpatrick Model",
        "Summative Assessment",
        "STEM / STEAM"
      ],
      "derivedFrom": "lt-def-formative-assessment",
      "explanation": "Compare: Kirkpatrick Model — A four-level framework for evaluating training effectiveness: Reaction, then Learning, then Behavior, then Results. Summative Assessment — Evaluation of learning after instruction — exams, final projects — to grade outcomes. Contrasted with formative assessment.",
      "uid": "s07ai1qgr5dv"
    },
    {
      "id": "czr-learning-theory-lt-def-summative-assessment",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "template": "___ — Evaluation of learning after instruction — exams, final projects — to grade outcomes. Contrasted with formative assessment",
      "answer": "Summative Assessment",
      "distractors": [
        "STEM / STEAM",
        "EdTech"
      ],
      "derivedFrom": "lt-def-summative-assessment",
      "explanation": "Compare: STEM / STEAM — Science, Technology, Engineering, (Arts), and Mathematics — disciplinary categories commonly addressed by edtech platforms. EdTech — Education technology — any technology used to facilitate or enhance learning.",
      "uid": "bmtkvh1mo0wuv"
    },
    {
      "id": "czr-learning-theory-lt-def-learner-analytics",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "template": "___ — The measurement, collection, analysis, and reporting of data about learners and their contexts in order to optimize learning",
      "answer": "Learner Analytics",
      "distractors": [
        "Formative Assessment",
        "EdTech",
        "Kirkpatrick Model"
      ],
      "derivedFrom": "lt-def-learner-analytics",
      "explanation": "Compare: Formative Assessment — Assessment during the learning process to provide feedback and adjust instruction. Low-stakes quizzes that trigger retrieval practice are an example. EdTech — Education technology — any technology used to facilitate or enhance learning.",
      "uid": "145nwut1t5ma8v"
    },
    {
      "id": "czr-learning-theory-lt-def-kirkpatrick",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "template": "___ — A four-level framework for evaluating training effectiveness: Reaction, then Learning, then Behavior, then Results",
      "answer": "Kirkpatrick Model",
      "distractors": [
        "Learner Analytics",
        "STEM / STEAM",
        "Summative Assessment"
      ],
      "derivedFrom": "lt-def-kirkpatrick",
      "explanation": "Compare: Learner Analytics — The measurement, collection, analysis, and reporting of data about learners and their contexts in order to optimize learning. STEM / STEAM — Science, Technology, Engineering, (Arts), and Mathematics — disciplinary categories commonly addressed by edtech platforms.",
      "uid": "17fpps57fgup3"
    },
    {
      "id": "czr-learning-theory-lt-def-xapi",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "template": "___ — A learning-data interoperability standard that captures experience statements across all learning contexts, not just the LMS",
      "answer": "xAPI / Tin Can API",
      "distractors": [
        "Learner Analytics",
        "STEM / STEAM",
        "EdTech"
      ],
      "derivedFrom": "lt-def-xapi",
      "explanation": "Compare: Learner Analytics — The measurement, collection, analysis, and reporting of data about learners and their contexts in order to optimize learning. STEM / STEAM — Science, Technology, Engineering, (Arts), and Mathematics — disciplinary categories commonly addressed by edtech platforms.",
      "uid": "1eoonkf1yv5hkd"
    },
    {
      "id": "czr-learning-theory-lt-def-mooc",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "template": "___ — A large-scale online course open to unlimited participation. Coursera, edX, and Udemy pioneered the model",
      "answer": "MOOC (Massive Open Online Course)",
      "distractors": [
        "Self-Determination Theory (SDT)",
        "Syllabus / Curriculum Map",
        "EdTech"
      ],
      "derivedFrom": "lt-def-mooc",
      "explanation": "Compare: Self-Determination Theory (SDT) — Deci & Ryan's theory (1985) naming three basic psychological needs for intrinsic motivation: autonomy, competence, and relatedness. A framework for engagement and gamification design.",
      "uid": "5o5vmyz5d0py"
    },
    {
      "id": "czr-learning-theory-lt-def-stem-steam",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "template": "___ — Science, Technology, Engineering, (Arts), and Mathematics — disciplinary categories commonly addressed by edtech platforms",
      "answer": "STEM / STEAM",
      "distractors": [
        "Learner Analytics",
        "Formative Assessment",
        "Summative Assessment"
      ],
      "derivedFrom": "lt-def-stem-steam",
      "explanation": "Compare: Learner Analytics — The measurement, collection, analysis, and reporting of data about learners and their contexts in order to optimize learning.",
      "uid": "nvosrb9vpkj1"
    },
    {
      "id": "czr-learning-theory-lt-def-edtech",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "template": "___ — Education technology — any technology used to facilitate or enhance learning",
      "answer": "EdTech",
      "distractors": [
        "Summative Assessment",
        "Learner Analytics",
        "STEM / STEAM"
      ],
      "derivedFrom": "lt-def-edtech",
      "explanation": "Compare: Summative Assessment — Evaluation of learning after instruction — exams, final projects — to grade outcomes. Contrasted with formative assessment.",
      "uid": "1hm049810c7j0s"
    },
    {
      "id": "czr-learning-theory-lt-def-sdt",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "template": "___ — Deci & Ryan's theory (1985) naming three basic psychological needs for intrinsic motivation: autonomy, competence, and relatedness. A framework for engagement and gamification design",
      "answer": "Self-Determination Theory (SDT)",
      "distractors": [
        "MOOC (Massive Open Online Course)",
        "Syllabus / Curriculum Map",
        "EdTech"
      ],
      "derivedFrom": "lt-def-sdt",
      "explanation": "Compare: MOOC (Massive Open Online Course) — A large-scale online course open to unlimited participation. Coursera, edX, and Udemy pioneered the model. Syllabus / Curriculum Map — A structured outline of learning objectives, content, sequence, and timeline for a course.",
      "uid": "etk4xq1167ma"
    },
    {
      "id": "czr-learning-theory-lt-def-syllabus",
      "shape": "cloze",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "template": "___ — A structured outline of learning objectives, content, sequence, and timeline for a course",
      "answer": "Syllabus / Curriculum Map",
      "distractors": [
        "MOOC (Massive Open Online Course)",
        "Self-Determination Theory (SDT)",
        "Summative Assessment"
      ],
      "derivedFrom": "lt-def-syllabus",
      "explanation": "Compare: MOOC (Massive Open Online Course) — A large-scale online course open to unlimited participation. Coursera, edX, and Udemy pioneered the model.",
      "uid": "mtxzd116o4tvb"
    },
    {
      "id": "czr-learning-theory-lt-def-operant-conditioning",
      "shape": "cloze",
      "tags": [
        "theory",
        "behaviorism",
        "vocabulary"
      ],
      "template": "___ — Skinner's principle that behavior is shaped by its consequences — reinforcement and punishment — rather than by internal mental states",
      "answer": "Operant conditioning",
      "distractors": [
        "Classical conditioning",
        "Assimilation",
        "Accommodation"
      ],
      "derivedFrom": "lt-def-operant-conditioning",
      "explanation": "Compare: Assimilation — Integrating new information into an existing schema without changing the schema itself. Accommodation — Modifying an existing schema to incorporate contradictory new information.",
      "uid": "17gxzj01x05gos"
    },
    {
      "id": "czr-learning-theory-lt-def-schema",
      "shape": "cloze",
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "template": "___ — A cognitive framework or category used to organize and interpret information",
      "answer": "Schema",
      "distractors": [
        "Assimilation",
        "Accommodation",
        "Equilibration"
      ],
      "derivedFrom": "lt-def-schema",
      "explanation": "Compare: Assimilation — Integrating new information into an existing schema without changing the schema itself. Accommodation — Modifying an existing schema to incorporate contradictory new information.",
      "uid": "xl27akathwus"
    },
    {
      "id": "czr-learning-theory-lt-def-assimilation",
      "shape": "cloze",
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "template": "___ — Integrating new information into an existing schema without changing the schema itself",
      "answer": "Assimilation",
      "distractors": [
        "Accommodation",
        "Jerome Bruner"
      ],
      "derivedFrom": "lt-def-assimilation",
      "explanation": "Compare: Accommodation — Modifying an existing schema to incorporate contradictory new information.",
      "uid": "1rdtmho1kf7fno"
    },
    {
      "id": "czr-learning-theory-lt-def-accommodation",
      "shape": "cloze",
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "template": "___ — Modifying an existing schema to incorporate contradictory new information",
      "answer": "Accommodation",
      "distractors": [
        "Jean Piaget",
        "Equilibration"
      ],
      "derivedFrom": "lt-def-accommodation",
      "explanation": "Compare: Jean Piaget — A Swiss psychologist who studied how children's thinking develops, anchoring the cognitivist view of learning. Equilibration — The drive to balance assimilation and accommodation, resolving the tension between old schemas and new information.",
      "uid": "1pl9vgv1ulnqcl"
    },
    {
      "id": "czr-learning-theory-lt-def-equilibration",
      "shape": "cloze",
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "template": "___ — The drive to balance assimilation and accommodation, resolving the tension between old schemas and new information",
      "answer": "Equilibration",
      "distractors": [
        "Adaptation",
        "Organization",
        "Decentration"
      ],
      "derivedFrom": "lt-def-equilibration",
      "uid": "1d0jdj01v1ucqc"
    },
    {
      "id": "czr-learning-theory-lt-def-zpd",
      "shape": "cloze",
      "tags": [
        "theory",
        "constructivism",
        "vocabulary"
      ],
      "template": "___ — Vygotsky's gap between what a learner can do independently and what they can achieve with guidance from a 'more knowledgeable other'",
      "answer": "Zone of Proximal Development (ZPD)",
      "distractors": [
        "Scaffolding",
        "Equilibration",
        "Metacognition"
      ],
      "derivedFrom": "lt-def-zpd",
      "explanation": "Compare: Scaffolding — Temporary instructional support — hints, prompts, models, worked examples — that helps a learner progress through their ZPD, withdrawn as competence grows.",
      "uid": "1e9sx0diudpzr"
    },
    {
      "id": "czr-learning-theory-lt-def-scaffolding",
      "shape": "cloze",
      "tags": [
        "theory",
        "constructivism",
        "vocabulary"
      ],
      "template": "___ — Temporary instructional support — hints, prompts, models, worked examples — that helps a learner progress through their ZPD, withdrawn as competence grows",
      "answer": "Scaffolding",
      "distractors": [
        "John Dewey",
        "Equilibration",
        "Schema"
      ],
      "derivedFrom": "lt-def-scaffolding",
      "explanation": "Compare: John Dewey — An American philosopher and education reformer of the early 20th century, central to pragmatism. Equilibration — The drive to balance assimilation and accommodation, resolving the tension between old schemas and new information.",
      "uid": "12bwz5l1nx8yy3"
    },
    {
      "id": "czr-learning-theory-lt-def-blooms-taxonomy",
      "shape": "cloze",
      "tags": [
        "theory",
        "blooms-taxonomy"
      ],
      "template": "___ — A hierarchy of six cognitive skill levels, from lower-order to higher-order: in the revised version, Remember, Understand, Apply, Analyze, Evaluate, Create",
      "answer": "Bloom's Taxonomy",
      "distractors": [
        "SOLO Taxonomy",
        "Webb's Depth of Knowledge",
        "Gagné's Nine Events"
      ],
      "derivedFrom": "lt-def-blooms-taxonomy",
      "uid": "hgmenmgcfkqu"
    },
    {
      "id": "czr-learning-theory-lt-def-two-sigma-problem",
      "shape": "cloze",
      "tags": [
        "theory",
        "two-sigma"
      ],
      "template": "___ — Bloom's 1984 challenge: one-to-one mastery tutoring lifts achievement by about two standard deviations, but is too costly to scale — so find a group method that matches it",
      "answer": "The 2 Sigma Problem",
      "distractors": [
        "Mastery learning",
        "George Miller",
        "Assimilation"
      ],
      "derivedFrom": "lt-def-two-sigma-problem",
      "explanation": "Compare: Mastery learning — An approach where students must reach a threshold (e.g. 90% on a test) before advancing; failures are treated as instructional gaps to correct, not student deficits. Assimilation — Integrating new information into an existing schema without changing the schema itself.",
      "uid": "h2cha2pcktsu"
    },
    {
      "id": "czr-learning-theory-lt-def-mastery-learning",
      "shape": "cloze",
      "tags": [
        "theory",
        "two-sigma",
        "mastery-learning"
      ],
      "template": "___ — An approach where students must reach a threshold (e.g. 90% on a test) before advancing; failures are treated as instructional gaps to correct, not student deficits",
      "answer": "Mastery learning",
      "distractors": [
        "Differentiated Instruction",
        "Problem-Based Learning",
        "Personalized Learning"
      ],
      "derivedFrom": "lt-def-mastery-learning",
      "explanation": "Compare: Differentiated Instruction — Tailoring content, process, or product to individual learner needs within a classroom setting — the human precursor to algorithmic personalization.",
      "uid": "1k2ngxpx1duh3"
    },
    {
      "id": "czr-learning-theory-lt-def-flow",
      "shape": "cloze",
      "tags": [
        "learning-science",
        "flow",
        "motivation"
      ],
      "template": "___ — An optimal experience of complete psychological immersion in a task, marked by intense enjoyment and effortless concentration",
      "answer": "Flow",
      "distractors": [
        "Autotelic activity",
        "Hebbian learning",
        "Intrinsic load"
      ],
      "derivedFrom": "lt-def-flow",
      "explanation": "Compare: Autotelic activity — An activity that is intrinsically rewarding — done for its own sake, not for an external payoff. The eighth hallmark of flow.",
      "uid": "muhfnx1ju6jtj"
    },
    {
      "id": "czr-learning-theory-lt-def-autotelic",
      "shape": "cloze",
      "tags": [
        "learning-science",
        "flow",
        "motivation"
      ],
      "template": "___ — An activity that is intrinsically rewarding — done for its own sake, not for an external payoff. The eighth hallmark of flow",
      "answer": "Autotelic activity",
      "distractors": [
        "Hebbian learning",
        "Germane load"
      ],
      "derivedFrom": "lt-def-autotelic",
      "explanation": "Compare: Hebbian learning — The principle that synaptic connections between neurons strengthen when they activate together — 'neurons that fire together, wire together.'. Germane load — Cognitive effort directed at building mental schemas — the productive load that designers should maximize.",
      "uid": "422cv1lu1wb1"
    },
    {
      "id": "czr-learning-theory-lt-def-dual-coding",
      "shape": "cloze",
      "tags": [
        "learning-science",
        "dual-coding",
        "memory"
      ],
      "template": "___ — Paivio's idea that humans have two interconnected memory systems — verbal and visual — and learning improves when both are engaged at once",
      "answer": "Dual Coding Theory",
      "distractors": [
        "Extraneous load",
        "Germane load",
        "Intrinsic load"
      ],
      "derivedFrom": "lt-def-dual-coding",
      "explanation": "Compare: Extraneous load — Cognitive load created by poor instructional design — unnecessary complexity that should be eliminated. Germane load — Cognitive effort directed at building mental schemas — the productive load that designers should maximize.",
      "uid": "85e2uik9h3ry"
    },
    {
      "id": "czr-learning-theory-lt-def-cognitive-load",
      "shape": "cloze",
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "template": "___ — Sweller's theory (1988) that working memory has limited capacity, so instruction must manage how much mental load the material imposes",
      "answer": "Cognitive Load Theory",
      "distractors": [
        "Extraneous load",
        "Germane load",
        "Intrinsic load"
      ],
      "derivedFrom": "lt-def-cognitive-load",
      "explanation": "Compare: Extraneous load — Cognitive load created by poor instructional design — unnecessary complexity that should be eliminated. Germane load — Cognitive effort directed at building mental schemas — the productive load that designers should maximize.",
      "uid": "1pjl6eo18tbo6o"
    },
    {
      "id": "czr-learning-theory-lt-def-intrinsic-load",
      "shape": "cloze",
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "template": "___ — The cognitive load that comes from the inherent complexity of the material itself — unavoidable, and set by the topic",
      "answer": "Intrinsic load",
      "distractors": [
        "Germane load",
        "Extraneous load",
        "Dual Coding Theory"
      ],
      "derivedFrom": "lt-def-intrinsic-load",
      "explanation": "Compare: Germane load — Cognitive effort directed at building mental schemas — the productive load that designers should maximize. Extraneous load — Cognitive load created by poor instructional design — unnecessary complexity that should be eliminated.",
      "uid": "3lvb3u1pl45ce"
    },
    {
      "id": "czr-learning-theory-lt-def-extraneous-load",
      "shape": "cloze",
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "template": "___ — Cognitive load created by poor instructional design — unnecessary complexity that should be eliminated",
      "answer": "Extraneous load",
      "distractors": [
        "Germane load",
        "Intrinsic load",
        "Dual Coding Theory"
      ],
      "derivedFrom": "lt-def-extraneous-load",
      "explanation": "Compare: Germane load — Cognitive effort directed at building mental schemas — the productive load that designers should maximize. Intrinsic load — The cognitive load that comes from the inherent complexity of the material itself — unavoidable, and set by the topic.",
      "uid": "12p98c5jopktz"
    },
    {
      "id": "czr-learning-theory-lt-def-germane-load",
      "shape": "cloze",
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "template": "___ — Cognitive effort directed at building mental schemas — the productive load that designers should maximize",
      "answer": "Germane load",
      "distractors": [
        "Extraneous load",
        "Intrinsic load",
        "Dual Coding Theory"
      ],
      "derivedFrom": "lt-def-germane-load",
      "explanation": "Compare: Extraneous load — Cognitive load created by poor instructional design — unnecessary complexity that should be eliminated. Intrinsic load — The cognitive load that comes from the inherent complexity of the material itself — unavoidable, and set by the topic.",
      "uid": "yxjjwj3a81c9"
    },
    {
      "id": "czr-learning-theory-lt-def-connectivism",
      "shape": "cloze",
      "tags": [
        "theory",
        "connectivism",
        "digital-age"
      ],
      "template": "___ — Siemens and Downes's 'learning theory for the digital age': learning is the process of creating connections between nodes in a network",
      "answer": "Connectivism",
      "distractors": [
        "Behaviorism",
        "Cognitivism",
        "Constructivism"
      ],
      "derivedFrom": "lt-def-connectivism",
      "uid": "7d6wed1qgyn93"
    },
    {
      "id": "czr-learning-theory-lt-def-udl",
      "shape": "cloze",
      "tags": [
        "instructional-design",
        "udl",
        "accessibility"
      ],
      "template": "___ — A neuroscience-based curriculum framework (Rose, CAST) that builds flexibility into learning from the outset rather than adding accommodations afterward",
      "answer": "Universal Design for Learning (UDL)",
      "distractors": [
        "ADDIE",
        "Dick & Carey Model",
        "Merrill's Principles of Instruction"
      ],
      "derivedFrom": "lt-def-udl",
      "explanation": "Compare: ADDIE — An instructional systems design framework structured as five phases: Analyze, Design, Develop, Implement, and Evaluate. Dick & Carey Model — This 1978 framework takes a systems view of instruction.",
      "uid": "usatwji4vlhd"
    },
    {
      "id": "czr-learning-theory-lt-def-method-of-loci",
      "shape": "cloze",
      "tags": [
        "memory",
        "mnemonics",
        "method-of-loci"
      ],
      "template": "___ — An ancient technique that places items to be memorized at spatial locations along a familiar mental journey; walking the path retrieves them in sequence",
      "answer": "Method of Loci (Memory Palace)",
      "distractors": [
        "Origin of the method of loci",
        "Keyword Method",
        "SRS (Spaced Repetition Software)"
      ],
      "derivedFrom": "lt-def-method-of-loci",
      "explanation": "Compare: Origin of the method of loci — Ancient Greece and Rome. Keyword Method — A language-learning mnemonic that links a foreign word's sound to a memorable image which bridges to the translation.",
      "uid": "1vvt1f5ro8nqz"
    },
    {
      "id": "czr-learning-theory-lt-def-keyword-method",
      "shape": "cloze",
      "tags": [
        "memory",
        "mnemonics",
        "keyword-method"
      ],
      "template": "___ — A language-learning mnemonic that links a foreign word's sound to a memorable image which bridges to the translation",
      "answer": "Keyword Method",
      "distractors": [
        "Method of Loci (Memory Palace)",
        "Chunking",
        "Dual Coding Theory"
      ],
      "derivedFrom": "lt-def-keyword-method",
      "explanation": "Compare: Method of Loci (Memory Palace) — An ancient technique that places items to be memorized at spatial locations along a familiar mental journey; walking the path retrieves them in sequence.",
      "uid": "d9qtbv1y2wo61"
    },
    {
      "id": "czr-learning-theory-lt-def-addie",
      "shape": "cloze",
      "tags": [
        "instructional-design",
        "addie"
      ],
      "template": "___ — An instructional systems design framework structured as five phases: Analyze, Design, Develop, Implement, and Evaluate",
      "answer": "ADDIE",
      "distractors": [
        "SAM (Successive Approximation Model)",
        "Dick & Carey Model",
        "Merrill's Principles of Instruction"
      ],
      "derivedFrom": "lt-def-addie",
      "explanation": "Compare: SAM (Successive Approximation Model) — Michael Allen built this framework in 2012 as a direct counterpoint to a decades-old linear model. Dick & Carey Model — This 1978 framework takes a systems view of instruction.",
      "uid": "1xtigqu1khb2a"
    },
    {
      "id": "czr-learning-theory-lt-def-backward-design",
      "shape": "cloze",
      "tags": [
        "instructional-design",
        "frameworks"
      ],
      "template": "___ — Wiggins and McTighe's approach in Understanding by Design: start from the desired learning outcomes, then work back to assessments and instruction",
      "answer": "Backward design",
      "distractors": [
        "Action Mapping",
        "SAM (Successive Approximation Model)",
        "Merrill's Principles of Instruction"
      ],
      "derivedFrom": "lt-def-backward-design",
      "explanation": "Compare: Action Mapping — Cathy Moore's 2008 performance-focused method that strips out 'nice to know' content and designs around what learners must actually do. SAM (Successive Approximation Model) — Michael Allen built this framework in 2012 as a direct counterpoint to a decades-old linear model.",
      "uid": "15toxa98dfryj"
    },
    {
      "id": "czr-learning-theory-lt-def-action-mapping",
      "shape": "cloze",
      "tags": [
        "instructional-design",
        "frameworks"
      ],
      "template": "___ — Cathy Moore's 2008 performance-focused method that strips out 'nice to know' content and designs around what learners must actually do",
      "answer": "Action Mapping",
      "distractors": [
        "Backward design",
        "SAM (Successive Approximation Model)",
        "Dick & Carey Model"
      ],
      "derivedFrom": "lt-def-action-mapping",
      "explanation": "Compare: Backward design — Wiggins and McTighe's approach in Understanding by Design: start from the desired learning outcomes, then work back to assessments and instruction.",
      "uid": "1okye6i190g4tq"
    },
    {
      "id": "czr-learning-theory-lt-def-socratic-method",
      "shape": "cloze",
      "tags": [
        "instructional-design",
        "socratic"
      ],
      "template": "___ — Teaching through guided, probing questions rather than direct answers, so the learner constructs the insight independently — yielding deeper encoding",
      "answer": "The Socratic method",
      "distractors": [
        "Direct instruction",
        "Lecture method",
        "Problem-Based Learning (PBL)"
      ],
      "derivedFrom": "lt-def-socratic-method",
      "explanation": "Compare: Problem-Based Learning (PBL) — An approach where students learn by investigating and solving an authentic, complex, open-ended problem — rooted in Dewey's experiential philosophy.",
      "uid": "2qckbq9o2n62"
    },
    {
      "id": "czr-learning-theory-lt-def-personalization-problem",
      "shape": "cloze",
      "tags": [
        "edtech",
        "brave-new-words",
        "personalization"
      ],
      "template": "___ — Great education requires understanding where a specific learner is, what they know, how they learn, and what engages them — historically only possible with expensive private tutors. Khan argues AI can democratize this at scale",
      "answer": "The personalization problem",
      "distractors": [
        "The ethical framework",
        "The contrarian review",
        "Beyond K-12"
      ],
      "derivedFrom": "lt-def-personalization-problem",
      "uid": "11rr24g1gpcdhs"
    },
    {
      "id": "czr-learning-theory-lt-def-khanmigo",
      "shape": "cloze",
      "tags": [
        "edtech",
        "khanmigo",
        "ai"
      ],
      "template": "___ — An AI tutoring assistant built on GPT-4 in collaboration with OpenAI. The name plays on \"Khan\" and the Spanish \"conmigo\" (\"with me\"). It uses the Socratic method, guides step-by-step, and never simply delivers answers",
      "answer": "Khanmigo",
      "distractors": [
        "MagicSchool AI",
        "Duolingo Max",
        "Google NotebookLM"
      ],
      "derivedFrom": "lt-def-khanmigo",
      "explanation": "Compare: MagicSchool AI — A teacher-tools platform for lesson planning, rubric generation, and cutting administrative work, keeping the educator central. Google NotebookLM — The canonical example of the 'Research Assistants' category in the AI-in-education taxonomy.",
      "uid": "1agd5gg18r6jcw"
    },
    {
      "id": "czr-learning-theory-lt-def-adaptive-learning",
      "shape": "cloze",
      "tags": [
        "platforms",
        "vocabulary"
      ],
      "template": "___ — Software that adjusts the content, sequence, and difficulty of instruction in real time based on each learner's performance history",
      "answer": "Adaptive learning system",
      "distractors": [
        "Learning management system (LMS)",
        "Learning Record Store (LRS)",
        "Student information system"
      ],
      "derivedFrom": "lt-def-adaptive-learning",
      "uid": "187c4dv1rtmw09"
    },
    {
      "id": "czr-learning-theory-lt-def-intelligent-tutoring",
      "shape": "cloze",
      "tags": [
        "evidence",
        "vocabulary"
      ],
      "template": "___ — A computer system that delivers individualized instruction and feedback, modeling both the subject and the learner's evolving understanding to guide them like a one-on-one tutor",
      "answer": "Intelligent tutoring system",
      "distractors": [
        "Learning management system (LMS)",
        "Learning Record Store (LRS)",
        "Student information system"
      ],
      "derivedFrom": "lt-def-intelligent-tutoring",
      "uid": "1dv7wg915wiesz"
    },
    {
      "id": "czr-learning-theory-lt-def-scorm",
      "shape": "cloze",
      "tags": [
        "standards",
        "lms",
        "vocabulary"
      ],
      "template": "___ — Sharable Content Object Reference Model (2001) — the original interoperability standard letting content work across different LMSs. Tracks completions and quiz scores only",
      "answer": "SCORM",
      "distractors": [
        "Backend store for xAPI statements",
        "LRS (Learning Record Store)"
      ],
      "derivedFrom": "lt-def-scorm",
      "explanation": "Compare: LRS (Learning Record Store) — The backend database that stores xAPI statements — a portable, durable repository of all learning activity across systems.",
      "uid": "1jnelv719exqkh"
    },
    {
      "id": "czr-learning-theory-lt-def-lrs",
      "shape": "cloze",
      "tags": [
        "standards",
        "lms",
        "vocabulary"
      ],
      "template": "___ — The backend database that stores xAPI statements — a portable, durable repository of all learning activity across systems",
      "answer": "LRS (Learning Record Store)",
      "distractors": [
        "SCORM",
        "LMS (Learning Management System)",
        "Learning Tools Interoperability (LTI)"
      ],
      "derivedFrom": "lt-def-lrs",
      "explanation": "Compare: SCORM — Sharable Content Object Reference Model (2001) — the original interoperability standard letting content work across different LMSs. Tracks completions and quiz scores only.",
      "uid": "j2cvr41hmlfr4"
    },
    {
      "id": "czr-learning-theory-lt-def-gamification",
      "shape": "cloze",
      "tags": [
        "gamification",
        "vocabulary"
      ],
      "template": "___ — The application of game design elements — points, badges, leaderboards, levels, narrative, challenges — to non-game contexts to increase engagement and motivation. Term coined by Nick Pelling in 2003",
      "answer": "Gamification",
      "distractors": [
        "Jesse Schell",
        "Thomas Malone"
      ],
      "derivedFrom": "lt-def-gamification",
      "uid": "1uj8g6xf9oq8b"
    },
    {
      "id": "cz-learning-theory-lt-fact-forgetting-curve",
      "shape": "cloze",
      "tags": [
        "memory",
        "forgetting-curve",
        "ebbinghaus"
      ],
      "template": "German psychologist **___** was among the first to study memory decay scientifically. Without review, we forget about **50% of new information within 30 minutes** and **70–80% within 24 hours**. This exponential decay is the **forgetting curve**.",
      "answer": "Hermann Ebbinghaus",
      "distractors": [
        "George Miller",
        "Ivan Pavlov",
        "B.F. Skinner"
      ],
      "derivedFrom": "lt-fact-forgetting-curve",
      "explanation": "Compare: Ivan Pavlov — A Russian physiologist whose work on the digestive system earned a Nobel Prize. B.F. Skinner — An early-20th-century American psychologist and the most influential figure in behaviorism.",
      "uid": "cy775z1xiq2j1"
    },
    {
      "id": "cz-learning-theory-lt-fact-affective-domain",
      "shape": "cloze",
      "tags": [
        "theory",
        "blooms-taxonomy",
        "affective-domain"
      ],
      "template": "A second handbook (___) covered the **affective domain** — attitudes, values, and motivations — across five levels: **Receiving, Responding, Valuing, Organizing, Characterizing.** Less discussed in edtech than the cognitive domain, but central to engagement design.",
      "answer": "1964",
      "distractors": [
        "1957",
        "1973",
        "1940"
      ],
      "derivedFrom": "lt-fact-affective-domain",
      "uid": "16ec8be487ej2"
    },
    {
      "id": "cz-learning-theory-lt-fact-two-sigma",
      "shape": "cloze",
      "tags": [
        "theory",
        "two-sigma"
      ],
      "template": "In **___**, Bloom reported that students tutored **one-to-one** with mastery techniques scored **two standard deviations** higher than conventionally taught peers — the average tutored student beat **98%** of the control class. The catch: 1:1 tutoring doesn't scale.",
      "answer": "1984",
      "distractors": [
        "1977",
        "1993",
        "1960"
      ],
      "derivedFrom": "lt-fact-two-sigma",
      "uid": "xbz7f918bkpy7"
    },
    {
      "id": "cz-learning-theory-lt-fact-flow-challenge-skill",
      "shape": "cloze",
      "tags": [
        "learning-science",
        "flow",
        "motivation"
      ],
      "template": "Mihaly **Csikszentmihalyi** described flow in ___. Its condition is precise: task **challenge must match the learner's skill**. Too easy breeds **boredom**; too hard breeds **anxiety**; the balance produces flow.",
      "answer": "1975",
      "distractors": [
        "1971",
        "1985",
        "1980"
      ],
      "derivedFrom": "lt-fact-flow-challenge-skill",
      "uid": "f7zy3j1sgxr99"
    },
    {
      "id": "mcq-c-learning-theory-lt-fact-flow-challenge-skill",
      "shape": "mcq",
      "tags": [
        "learning-science",
        "flow",
        "motivation"
      ],
      "prompt": {
        "modality": "text",
        "value": "Mihaly **Csikszentmihalyi** described flow in ___. Its condition is precise: task **challenge must match the learner's skill**. Too easy breeds **boredom**; too hard breeds **anxiety**; the balance produces flow."
      },
      "options": [
        {
          "modality": "text",
          "value": "1975"
        },
        {
          "modality": "text",
          "value": "1980"
        },
        {
          "modality": "text",
          "value": "1971"
        },
        {
          "modality": "text",
          "value": "1985"
        }
      ],
      "correctIndex": 0,
      "derivedFrom": "lt-fact-flow-challenge-skill",
      "uid": "xpzxqyhznm8m"
    },
    {
      "id": "cz-learning-theory-lt-fact-addie-origin",
      "shape": "cloze",
      "tags": [
        "instructional-design",
        "addie",
        "history"
      ],
      "template": "**ADDIE** was developed in **1975** at **___** Center for Educational Technology — for the **U.S. Army**. Decades later it remains the dominant **instructional systems design (ISD)** framework worldwide. The name is just an acronym for its five phases.",
      "answer": "Florida State University",
      "distractors": [
        "Indiana University",
        "University of Michigan",
        "Ohio State University"
      ],
      "derivedFrom": "lt-fact-addie-origin",
      "uid": "i1179m1eldwxa"
    },
    {
      "id": "cz-learning-theory-lt-fact-khanmigo-socratic",
      "shape": "cloze",
      "tags": [
        "instructional-design",
        "socratic",
        "edtech"
      ],
      "template": "___ built **Khanmigo** to embody Socratic principles: it guides students *through* their learning rather than just handing over answers. That operationalizes a constructivist insight — knowledge a learner builds is more durable than knowledge merely received.",
      "answer": "Sal Khan",
      "distractors": [
        "Luis von Ahn",
        "Sebastian Thrun",
        "Sam Altman"
      ],
      "derivedFrom": "lt-fact-khanmigo-socratic",
      "uid": "b3dx741k2in3s"
    },
    {
      "id": "cz-learning-theory-lt-fact-khanmigo-name",
      "shape": "cloze",
      "tags": [
        "edtech",
        "khanmigo",
        "ai"
      ],
      "template": "**Khanmigo** is a play on \"Khan\" and the Spanish word **conmigo** — \"with me.\" The pun captures the pitch: a tutor that learns alongside the student rather than lecturing at them. It was built on **GPT-4** with OpenAI as ___ proof of concept.",
      "answer": "Khan Academy",
      "distractors": [
        "Coursera",
        "Duolingo",
        "Udacity"
      ],
      "derivedFrom": "lt-fact-khanmigo-name",
      "explanation": "Compare: Duolingo — A popular language-learning app whose proprietary adaptive model orchestrates the entire lesson experience.",
      "uid": "1u188bi1y4an0q"
    },
    {
      "id": "cz-learning-theory-lt-fact-beyond-classroom",
      "shape": "cloze",
      "tags": [
        "edtech",
        "brave-new-words",
        "implications"
      ],
      "template": "Khan does not confine the argument to schools. **___** explores AI's implications for **college admissions**, the **workplace**, and **civic participation** — treating personalized AI as infrastructure for learning across a whole life, not just the K-12 years.",
      "answer": "Brave New Words",
      "distractors": [
        "The Diamond Age",
        "Ender's Game",
        "The Fun They Had"
      ],
      "derivedFrom": "lt-fact-beyond-classroom",
      "explanation": "Compare: The Diamond Age — One of three works of speculative fiction Khan credits with shaping his vision of personalized instruction for any child. Ender's Game — One of three speculative-fiction works Khan names as inspiration for his 2024 book on AI and learning.",
      "uid": "4bq8ak1o60918"
    },
    {
      "id": "tf-t-learning-theory-lt-pair-anki",
      "shape": "trueFalse",
      "tags": [
        "memory",
        "spaced-repetition",
        "edtech"
      ],
      "statement": "\"Anki / SuperMemo\" refers to \"SRS apps that schedule reviews at the optimal interval\".",
      "isTrue": true,
      "why": "Anki and SuperMemo are SRS apps that schedule each review at the optimal interval. Spaced repetition is the principle they implement: study distributed over expanding gaps beats the same hours spent cramming in one sitting.",
      "derivedFrom": "lt-pair-anki",
      "uid": "1k2txb2a5ckmi"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-roediger-butler",
      "shape": "trueFalse",
      "tags": [
        "retrieval",
        "testing-effect",
        "references"
      ],
      "statement": "\"Roediger & Butler (2011)\" refers to \"A child finds a classroom of other children an exotic concept\".",
      "isTrue": false,
      "why": "Asimov's 'The Fun They Had' is the story where a child finds a classroom of other children an exotic concept. Roediger and Butler (2011) is a research review instead, on retrieval practice's critical role in long-term retention.",
      "derivedFrom": "lt-pair-roediger-butler",
      "uid": "1qgv9wk1i1jt8c"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-skinner",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "behaviorism",
        "theorist"
      ],
      "statement": "B.F. Skinner is \"Early behaviorism\".",
      "isTrue": false,
      "why": "John Watson is the name attached to early behaviorism. B.F. Skinner came later and is paired with operant conditioning: behaviour shaped by its consequences, reinforcement and punishment, rather than by internal mental states.",
      "derivedFrom": "lt-pair-skinner",
      "uid": "524hlw1gum4vw"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-pavlov",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "behaviorism",
        "theorist"
      ],
      "statement": "Ivan Pavlov is \"Chunking / 7±2 rule\".",
      "isTrue": false,
      "why": "George Miller is the name behind chunking and the 7±2 rule. Ivan Pavlov belongs to a different tradition entirely: stimulus-response conditioning, the dogs that learned to salivate at a bell.",
      "derivedFrom": "lt-pair-pavlov",
      "uid": "1jzt1o418yulrg"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-watson",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "behaviorism",
        "theorist"
      ],
      "statement": "John Watson is \"Learn by doing\".",
      "isTrue": false,
      "why": "Learn by doing is John Dewey's phrase, the root of experiential education. John Watson founded early behaviorism, which pushed psychology toward observable behaviour and away from introspection.",
      "derivedFrom": "lt-pair-watson",
      "uid": "2joje91r4prv"
    },
    {
      "id": "tf-t-learning-theory-lt-pair-miller",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "cognitivism",
        "theorist"
      ],
      "statement": "George Miller is \"Chunking / 7±2 rule\".",
      "isTrue": true,
      "why": "George Miller is paired with chunking and the 7±2 rule — the claim that working memory holds only a handful of items at once. Working memory is the system that limit describes, and cognitive load theory is built on it.",
      "derivedFrom": "lt-pair-miller",
      "uid": "k5utan6to7v1"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-dewey",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "constructivism",
        "theorist"
      ],
      "statement": "John Dewey is \"Early behaviorism\".",
      "isTrue": false,
      "why": "Early behaviorism is John Watson's contribution. John Dewey stands for learn by doing — the experiential philosophy that later grew into problem-based learning and the project classroom.",
      "derivedFrom": "lt-pair-dewey",
      "uid": "19lhtqh1ijn24b"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-remember-verbs",
      "shape": "trueFalse",
      "tags": [
        "blooms-taxonomy",
        "action-verbs"
      ],
      "statement": "\"Remember\" refers to \"use, execute, implement, solve\".",
      "isTrue": false,
      "why": "Use, execute, implement and solve are the verbs of Apply, Bloom's third level. Remember sits at the bottom of the taxonomy, and its verbs are define, list, recall and identify.",
      "derivedFrom": "lt-pair-remember-verbs",
      "uid": "h7ignf1dyx4dt"
    },
    {
      "id": "tf-t-learning-theory-lt-pair-apply-verbs",
      "shape": "trueFalse",
      "tags": [
        "blooms-taxonomy",
        "action-verbs"
      ],
      "statement": "\"Apply\" refers to \"use, execute, implement, solve\".",
      "isTrue": true,
      "why": "Apply is the third level of Bloom's revised taxonomy, and its verbs are use, execute, implement and solve. Remember is the level beneath it, with define, list, recall and identify.",
      "derivedFrom": "lt-pair-apply-verbs",
      "uid": "1izprth8r4027"
    },
    {
      "id": "tf-t-learning-theory-lt-pair-memory-palace-origin",
      "shape": "trueFalse",
      "tags": [
        "memory",
        "mnemonics",
        "method-of-loci"
      ],
      "statement": "Ancient Greece and Rome is \"Origin of the method of loci\".",
      "isTrue": true,
      "why": "Ancient Greece and Rome are where the method of loci originates, in the training of orators. The technique places items at spatial points along a familiar mental journey; walking the path retrieves them in order.",
      "derivedFrom": "lt-pair-memory-palace-origin",
      "uid": "c1mlkb1dml2eh"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-addie-analyze",
      "shape": "trueFalse",
      "tags": [
        "instructional-design",
        "addie"
      ],
      "statement": "\"Analyze (ADDIE)\" refers to \"Build the content, activities, and assessments\".",
      "isTrue": false,
      "why": "Building the content, activities and assessments is Develop, the third ADDIE phase. Analyze is the first: identify goals, audience, prior knowledge and constraints before anything gets built.",
      "derivedFrom": "lt-pair-addie-analyze",
      "uid": "1jdu3dtcvoh37"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-addie-design",
      "shape": "trueFalse",
      "tags": [
        "instructional-design",
        "addie"
      ],
      "statement": "\"Design (ADDIE)\" refers to \"Build the content, activities, and assessments\".",
      "isTrue": false,
      "why": "Building the content, activities and assessments is the Develop phase. Design comes before it and defines objectives, assessment, sequencing and modalities — the blueprint rather than the construction.",
      "derivedFrom": "lt-pair-addie-design",
      "uid": "1fn59nx1t9uurz"
    },
    {
      "id": "tf-t-learning-theory-lt-pair-addie-develop",
      "shape": "trueFalse",
      "tags": [
        "instructional-design",
        "addie"
      ],
      "statement": "\"Develop (ADDIE)\" refers to \"Build the content, activities, and assessments\".",
      "isTrue": true,
      "why": "Develop is the ADDIE phase where the content, activities and assessments actually get built. Design is the phase before it, fixing objectives, assessment, sequencing and modalities first.",
      "derivedFrom": "lt-pair-addie-develop",
      "uid": "1g1y0d31s09f8l"
    },
    {
      "id": "tf-t-learning-theory-lt-pair-merrill",
      "shape": "trueFalse",
      "tags": [
        "instructional-design",
        "frameworks"
      ],
      "statement": "\"Merrill's Principles (2002)\" refers to \"Task-centered 'first principles' of effective design\".",
      "isTrue": true,
      "why": "Merrill's Principles (2002) are the task-centered 'first principles' of effective design. ADDIE is the older process framework alongside them: Analyze, Design, Develop, Implement, Evaluate.",
      "derivedFrom": "lt-pair-merrill",
      "uid": "mj4pyn1dcvwf9"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-diamond-age",
      "shape": "trueFalse",
      "tags": [
        "edtech",
        "brave-new-words",
        "sci-fi"
      ],
      "statement": "\"The Diamond Age (Neal Stephenson)\" refers to \"Personalized, challenge-driven simulation learning\".",
      "isTrue": false,
      "why": "Personalized, challenge-driven simulation learning is Ender's Game. The Diamond Age is Neal Stephenson's novel in which an AI tutor, the Primer, becomes a poor girl's greatest educational resource.",
      "derivedFrom": "lt-pair-diamond-age",
      "uid": "1ndf38zlvcck9"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-enders-game",
      "shape": "trueFalse",
      "tags": [
        "edtech",
        "brave-new-words",
        "sci-fi"
      ],
      "statement": "Ender's Game is \"A child finds a classroom of other children an exotic concept\".",
      "isTrue": false,
      "why": "A child finding a classroom of other children an exotic concept is Asimov's 'The Fun They Had'. Ender's Game is the one about personalized, challenge-driven simulation learning — the battle room as adaptive curriculum.",
      "derivedFrom": "lt-pair-enders-game",
      "uid": "b7x54e1czo51u"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-fun-they-had",
      "shape": "trueFalse",
      "tags": [
        "edtech",
        "brave-new-words",
        "sci-fi"
      ],
      "statement": "\"Asimov's 'The Fun They Had'\" refers to \"Personalized, challenge-driven simulation learning\".",
      "isTrue": false,
      "why": "Ender's Game is the story of personalized, challenge-driven simulation learning. Asimov's 'The Fun They Had' runs the other way: a child taught by a machine finds a classroom of other children an exotic idea.",
      "derivedFrom": "lt-pair-fun-they-had",
      "uid": "68rcz7lfyjmx"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-tutors-khanmigo",
      "shape": "trueFalse",
      "tags": [
        "taxonomy",
        "edtech"
      ],
      "statement": "AI Tutors is \"Upskilling and corporate training (Sana, Coursera+Udemy, Multiverse)\".",
      "isTrue": false,
      "why": "Upskilling and corporate training — Sana, Coursera, Udemy, Multiverse — is the Enterprise and Workforce category. AI Tutors covers adaptive, conversational one-to-one instruction: Khanmigo, Synthesis, LearnLM.",
      "derivedFrom": "lt-pair-tutors-khanmigo",
      "uid": "7h1kucydu1u"
    },
    {
      "id": "tf-t-learning-theory-lt-pair-teachertools-magicschool",
      "shape": "trueFalse",
      "tags": [
        "taxonomy",
        "edtech"
      ],
      "statement": "Teacher Tools is \"Lesson planning, rubric generation, admin reduction (MagicSchool, Diffit)\".",
      "isTrue": true,
      "why": "Teacher Tools is the category covering lesson planning, rubric generation and admin reduction — MagicSchool, Diffit. AI Tutors is the neighbouring category, aimed at the learner rather than the teacher.",
      "derivedFrom": "lt-pair-teachertools-magicschool",
      "uid": "o3d99kzrriqg"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-language-duolingo",
      "shape": "trueFalse",
      "tags": [
        "taxonomy",
        "edtech"
      ],
      "statement": "Language Learning is \"Upskilling and corporate training (Sana, Coursera+Udemy, Multiverse)\".",
      "isTrue": false,
      "why": "Language Learning is the category for adaptive vocabulary and conversation practice — Duolingo, Lingokids. Enterprise and Workforce is the one covering upskilling and corporate training: Sana, Coursera, Udemy, Multiverse.",
      "derivedFrom": "lt-pair-language-duolingo",
      "uid": "fgzz4f14lob85"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-research-notebooklm",
      "shape": "trueFalse",
      "tags": [
        "taxonomy",
        "edtech"
      ],
      "statement": "Research Assistants is \"Adaptive vocabulary and conversation practice (Duolingo, Lingokids)\".",
      "isTrue": false,
      "why": "Adaptive vocabulary and conversation practice — Duolingo, Lingokids — is Language Learning. Research Assistants is the category for document synthesis and multi-source knowledge: NotebookLM, Perplexity.",
      "derivedFrom": "lt-pair-research-notebooklm",
      "uid": "5a4o5l3derp7"
    },
    {
      "id": "tf-t-learning-theory-lt-pair-duolingo-birdbrain",
      "shape": "trueFalse",
      "tags": [
        "platforms",
        "language-learning"
      ],
      "statement": "Duolingo BirdBrain is \"Proprietary AI that sequences and personalizes lessons from performance history\".",
      "isTrue": true,
      "why": "Duolingo BirdBrain is the proprietary AI that sequences and personalizes lessons from a learner's performance history. Language Learning is the wider category it sits in, alongside Lingokids and the rest.",
      "derivedFrom": "lt-pair-duolingo-birdbrain",
      "uid": "1m945rmnvmdgm"
    },
    {
      "id": "tf-t-learning-theory-lt-pair-scorm-tracks",
      "shape": "trueFalse",
      "tags": [
        "standards",
        "lms"
      ],
      "statement": "\"SCORM\" refers to \"Tracks completions and quiz scores only\".",
      "isTrue": true,
      "why": "SCORM tracks completions and quiz scores, and nothing finer. An LRS is the backend store for xAPI statements, which is where the granular record of what a learner actually did ends up instead.",
      "derivedFrom": "lt-pair-scorm-tracks",
      "uid": "l62osb1gl7gmh"
    },
    {
      "id": "tf-f-learning-theory-lt-pair-lrs-role",
      "shape": "trueFalse",
      "tags": [
        "standards",
        "lms"
      ],
      "statement": "\"LRS\" refers to \"Tracks completions and quiz scores only\".",
      "isTrue": false,
      "why": "Tracking completions and quiz scores only is SCORM, the 2001 interoperability standard. An LRS is the backend store for xAPI statements — the durable record of activity across systems, not just the LMS.",
      "derivedFrom": "lt-pair-lrs-role",
      "uid": "pcsf4fwf1del"
    },
    {
      "id": "tf-df-learning-theory-lt-def-hebbian",
      "shape": "trueFalse",
      "tags": [
        "learning-science",
        "neuroscience"
      ],
      "statement": "Autotelic activity: The principle that synaptic connections between neurons strengthen when they activate together — 'neurons that fire together, wire together.'",
      "isTrue": false,
      "why": "Hebbian learning is the principle that synapses strengthen when neurons activate together — neurons that fire together, wire together. An autotelic activity is something else: one done for its own sake, the eighth hallmark of flow.",
      "derivedFrom": "lt-def-hebbian",
      "uid": "18dds061li5lvu"
    },
    {
      "id": "tf-df-learning-theory-lt-def-forgetting-curve",
      "shape": "trueFalse",
      "tags": [
        "memory",
        "forgetting-curve"
      ],
      "statement": "Keyword Method: Ebbinghaus's finding that memory of new information decays exponentially over time without review, losing most of it within a day.",
      "isTrue": false,
      "why": "The forgetting curve is Ebbinghaus's finding that memory of new information decays exponentially without review, most of it gone within a day. The Keyword Method is a mnemonic: a foreign word's sound hooked to an image that bridges to the translation.",
      "derivedFrom": "lt-def-forgetting-curve",
      "uid": "1lo0lud100bqtr"
    },
    {
      "id": "tf-d-learning-theory-lt-def-spaced-repetition",
      "shape": "trueFalse",
      "tags": [
        "memory",
        "spaced-repetition"
      ],
      "statement": "Spaced repetition: Distributing study sessions over expanding intervals, which produces far better retention than the same time spent cramming in one sitting.",
      "isTrue": true,
      "why": "Spaced repetition distributes study over expanding intervals, which retains far more than the same hours spent cramming in one sitting. SRS is the software layer on top: Anki and SuperMemo timing each review for you.",
      "derivedFrom": "lt-def-spaced-repetition",
      "uid": "gsir1p1seho6n"
    },
    {
      "id": "tf-d-learning-theory-lt-def-srs",
      "shape": "trueFalse",
      "tags": [
        "memory",
        "spaced-repetition",
        "edtech"
      ],
      "statement": "SRS (Spaced Repetition Software): Software like Anki and SuperMemo that algorithmically schedules each review at the moment of maximum forgetting — the optimal interval.",
      "isTrue": true,
      "why": "SRS is software like Anki and SuperMemo that algorithmically schedules each review at the moment of maximum forgetting. Spaced repetition is the underlying finding it automates — expanding gaps beat massed practice.",
      "derivedFrom": "lt-def-srs",
      "uid": "17yabdwlfik5g"
    },
    {
      "id": "tf-d-learning-theory-lt-def-retrieval-practice",
      "shape": "trueFalse",
      "tags": [
        "retrieval",
        "testing-effect"
      ],
      "statement": "Retrieval practice: Strengthening memory by actively recalling information rather than re-exposing yourself to it; the mechanism behind the testing effect.",
      "isTrue": true,
      "why": "Retrieval practice strengthens memory by actively recalling information rather than re-exposing yourself to it; it is the mechanism behind the testing effect. Spaced repetition schedules those retrievals at widening intervals.",
      "derivedFrom": "lt-def-retrieval-practice",
      "uid": "112cr6alrrfku"
    },
    {
      "id": "tf-d-learning-theory-lt-def-als",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Adaptive Learning System (ALS): Software that dynamically adjusts content difficulty, sequence, and modality based on ongoing learner performance data.",
      "isTrue": true,
      "why": "An adaptive learning system dynamically adjusts content difficulty, sequence and modality from ongoing performance data. An intelligent tutoring system goes further, modelling domain and learner to teach without a human in the loop.",
      "derivedFrom": "lt-def-als",
      "uid": "v8kwn7ejjn7l"
    },
    {
      "id": "tf-d-learning-theory-lt-def-agentic-ai",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Agentic AI: Autonomous AI that can plan, take actions, use tools, and pursue goals across multiple steps with minimal human intervention.",
      "isTrue": true,
      "why": "Agentic AI plans, acts, uses tools and pursues goals across multiple steps with minimal human intervention; in education it can run planning, generation, assessment and feedback in one loop. Generative AI only produces the content.",
      "derivedFrom": "lt-def-agentic-ai",
      "uid": "1mreovu1wjw9ta"
    },
    {
      "id": "tf-df-learning-theory-lt-def-generative-ai",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Zero-Shot Learning (AI): AI systems that produce novel text, images, or audio.",
      "isTrue": false,
      "why": "Generative AI is the family of systems producing novel text, images or audio — dynamic content, conversational tutoring, feedback at scale. Zero-shot learning is a narrower capability: performing a task never explicitly trained on.",
      "derivedFrom": "lt-def-generative-ai",
      "uid": "1adc1211da3xcb"
    },
    {
      "id": "tf-df-learning-theory-lt-def-bkt",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Zero-Shot Learning (AI): A probabilistic model used in intelligent tutoring systems to estimate the probability that a learner has mastered a skill, updating that estimate after each response.",
      "isTrue": false,
      "why": "Bayesian Knowledge Tracing is the probabilistic model estimating the chance a learner has mastered a skill, updating after every response. Zero-shot learning is an LLM capability instead: handling a task it was never explicitly trained on.",
      "derivedFrom": "lt-def-bkt",
      "uid": "1mvlni2u3p9e6"
    },
    {
      "id": "tf-df-learning-theory-lt-def-dkt",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Zero-Shot Learning (AI): A recurrent neural network (LSTM) approach to knowledge tracing that models learner knowledge as a hidden state evolving with each interaction (Piech et al., 2015).",
      "isTrue": false,
      "why": "Deep Knowledge Tracing is the LSTM approach modelling learner knowledge as a hidden state evolving with each interaction (Piech et al., 2015). Zero-shot learning is unrelated: generalizing to a task from broad pre-training alone.",
      "derivedFrom": "lt-def-dkt",
      "uid": "1s4epkb7hgz1d"
    },
    {
      "id": "tf-d-learning-theory-lt-def-knowledge-state",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Knowledge State: A model representing what a specific learner currently knows and doesn't know within a domain, updated continuously by the system.",
      "isTrue": true,
      "why": "A knowledge state is the model of what one specific learner currently knows and does not know in a domain, updated continuously. Bayesian Knowledge Tracing is one common way of estimating it, response by response.",
      "derivedFrom": "lt-def-knowledge-state",
      "uid": "1c1tsv81unlwm4"
    },
    {
      "id": "tf-d-learning-theory-lt-def-its",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Intelligent Tutoring System (ITS): Software that provides personalized instruction and feedback without a human teacher in the loop, using models of the domain, the learner, and pedagogy.",
      "isTrue": true,
      "why": "An intelligent tutoring system gives personalized instruction and feedback with no human teacher in the loop, using models of domain, learner and pedagogy. An adaptive learning system adjusts difficulty but does not tutor.",
      "derivedFrom": "lt-def-its",
      "uid": "rhdwbd8u2a7n"
    },
    {
      "id": "tf-df-learning-theory-lt-def-cognitive-tutor",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Affective Computing: An AI tutoring system developed at Carnegie Mellon that models student cognition and gives personalized hints and feedback within a specific domain, originally mathematics.",
      "isTrue": false,
      "why": "Cognitive Tutor is the Carnegie Mellon system that models student cognition and gives hints inside a specific domain, originally mathematics. Affective computing reads emotion instead — frustration, boredom, curiosity — and adapts to it.",
      "derivedFrom": "lt-def-cognitive-tutor",
      "uid": "yzwayy1hzsyse"
    },
    {
      "id": "tf-d-learning-theory-lt-def-algorithm-sequencing",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Algorithm-Based Sequencing: Using ML models (often BKT or DKT) to predict learner knowledge states and determine the optimal next item to present.",
      "isTrue": true,
      "why": "Algorithm-based sequencing uses ML models, often BKT or DKT, to predict knowledge states and pick the optimal next item. Human-in-the-loop is the safeguard around it: people review or override what the system proposes.",
      "derivedFrom": "lt-def-algorithm-sequencing",
      "uid": "1vygkt7yojjr"
    },
    {
      "id": "tf-df-learning-theory-lt-def-zero-shot",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Human-in-the-Loop (HITL): An LLM's ability to perform a task it was not explicitly trained on, generalizing from broad pre-training — relevant to generating curriculum for rare or niche subjects.",
      "isTrue": false,
      "why": "Zero-shot learning is an LLM performing a task it was never explicitly trained on, generalizing from broad pre-training. Human-in-the-loop is a design pattern, not a capability: people review, approve or override outputs before delivery.",
      "derivedFrom": "lt-def-zero-shot",
      "uid": "1w3ik1m1hwkhp2"
    },
    {
      "id": "tf-d-learning-theory-lt-def-affective-computing",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Affective Computing: AI systems that detect and respond to learner emotions — frustration, boredom, curiosity — to adapt instruction accordingly.",
      "isTrue": true,
      "why": "Affective computing detects and responds to learner emotion — frustration, boredom, curiosity — and adapts instruction to it. Cognitive Tutor models cognition rather than affect, giving domain hints from a model of the student's thinking.",
      "derivedFrom": "lt-def-affective-computing",
      "uid": "4zf4341tu5pvk"
    },
    {
      "id": "tf-df-learning-theory-lt-def-knowledge-graph",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Bayesian Knowledge Tracing (BKT): A structured representation of learning objectives and their dependencies, used by adaptive systems to find prerequisite relationships and optimal learning paths.",
      "isTrue": false,
      "why": "A curriculum or knowledge graph is the structured map of learning objectives and their dependencies, used to find prerequisites and optimal paths. Bayesian Knowledge Tracing estimates mastery probability instead, after each response.",
      "derivedFrom": "lt-def-knowledge-graph",
      "uid": "1ld796i1qx6xv2"
    },
    {
      "id": "tf-df-learning-theory-lt-def-ontology",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Cognitive Tutor: A formal representation of knowledge and the relationships between concepts in a domain, used to structure curriculum graphs and content recommendations.",
      "isTrue": false,
      "why": "An ontology is the formal representation of a domain's concepts and the relations between them, used to structure curriculum graphs. Cognitive Tutor is a system rather than a representation: Carnegie Mellon's domain tutor, originally for mathematics.",
      "derivedFrom": "lt-def-ontology",
      "uid": "n5h14d2i573r"
    },
    {
      "id": "tf-d-learning-theory-lt-def-prompt-engineering",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Prompt Engineering: Designing the inputs given to LLMs so they produce the desired instructional outputs — a practical skill for edtech builders working with foundation models.",
      "isTrue": true,
      "why": "Prompt engineering is designing the inputs given to LLMs so they produce the instructional output you wanted — a practical skill for edtech builders. Zero-shot learning is the model-side capability those prompts lean on.",
      "derivedFrom": "lt-def-prompt-engineering",
      "uid": "1l5bc99266o13"
    },
    {
      "id": "tf-df-learning-theory-lt-def-hitl",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "ai-adaptive"
      ],
      "statement": "Algorithm-Based Sequencing: AI system design where humans review, approve, or override AI outputs before delivery — used in responsible edtech to catch errors and ensure quality.",
      "isTrue": false,
      "why": "Human-in-the-loop is the design pattern where people review, approve or override AI output before it reaches a learner. Algorithm-based sequencing is the machinery being overseen: ML models choosing the optimal next item.",
      "derivedFrom": "lt-def-hitl",
      "uid": "1knx3ug1lcn0q8"
    },
    {
      "id": "tf-df-learning-theory-lt-def-metacognition",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "statement": "Transfer of Learning: Thinking about one's own thinking — awareness of one's learning process, knowledge gaps, and strategies.",
      "isTrue": false,
      "why": "Metacognition is thinking about one's own thinking — awareness of your learning process, gaps and strategies. Transfer of learning is a different target: applying what was learned in one context to a genuinely new one.",
      "derivedFrom": "lt-def-metacognition",
      "uid": "1ohilkfrqgqed"
    },
    {
      "id": "tf-df-learning-theory-lt-def-differentiated-instruction",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "statement": "Scaffolded Curriculum: Tailoring content, process, or product to individual learner needs within a classroom setting — the human precursor to algorithmic personalization.",
      "isTrue": false,
      "why": "Differentiated instruction tailors content, process or product to individual learners inside a classroom — the human precursor to algorithmic personalization. A scaffolded curriculum instead fades support as competence grows, per Vygotsky's ZPD.",
      "derivedFrom": "lt-def-differentiated-instruction",
      "uid": "a6e4rf1up1n29"
    },
    {
      "id": "tf-df-learning-theory-lt-def-personalized-learning",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "statement": "Differentiated Instruction: An instructional approach that tailors pace, content, sequence, and modality to the individual learner's needs, goals, and learning style.",
      "isTrue": false,
      "why": "Personalized learning tailors pace, content, sequence and modality to the individual learner's goals and needs. Differentiated instruction is its classroom-era ancestor: one teacher varying content, process or product across a room.",
      "derivedFrom": "lt-def-personalized-learning",
      "uid": "lqfw8n1g45f2d"
    },
    {
      "id": "tf-d-learning-theory-lt-def-microlearning",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "statement": "Microlearning: Delivering content in short, focused bursts of 2–10 minutes, each built for a single learning objective.",
      "isTrue": true,
      "why": "Microlearning delivers content in short focused bursts of two to ten minutes, each built around a single objective, exploiting attention spans and mobile habits. Chunking is the cognitive principle underneath that sizing.",
      "derivedFrom": "lt-def-microlearning",
      "uid": "1gxb7b43e6kao"
    },
    {
      "id": "tf-df-learning-theory-lt-def-multimodal-learning",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "statement": "Metacognition: Engaging multiple sensory channels — visual, auditory, kinesthetic — together to deepen encoding.",
      "isTrue": false,
      "why": "Multimodal learning engages several sensory channels at once — visual, auditory, kinesthetic — to deepen encoding, grounded in dual coding and cognitive load theory. Metacognition is awareness of your own thinking, not a matter of channels.",
      "derivedFrom": "lt-def-multimodal-learning",
      "uid": "7mt8ihc8uxgz"
    },
    {
      "id": "tf-d-learning-theory-lt-def-pbl",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "statement": "Problem-Based Learning (PBL): An approach where students learn by investigating and solving an authentic, complex, open-ended problem — rooted in Dewey's experiential philosophy.",
      "isTrue": true,
      "why": "Problem-based learning has students learn by investigating and solving an authentic, complex, open-ended problem, rooted in Dewey's experiential philosophy. An adaptive learning system is the opposite pole: software tuning difficulty live.",
      "derivedFrom": "lt-def-pbl",
      "uid": "1dzb19w1l0482c"
    },
    {
      "id": "tf-df-learning-theory-lt-def-scaffolded-curriculum",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "statement": "Differentiated Instruction: A structured learning sequence that provides appropriate support at each level and fades assistance as competence grows — directly implementing Vygotsky's ZPD.",
      "isTrue": false,
      "why": "A scaffolded curriculum is a structured sequence supplying support at each level and withdrawing it as competence grows — Vygotsky's ZPD made into a syllabus. Differentiated instruction varies content across learners rather than across time.",
      "derivedFrom": "lt-def-scaffolded-curriculum",
      "uid": "87ahwc1ji2iis"
    },
    {
      "id": "tf-d-learning-theory-lt-def-cbe",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "statement": "Competency-Based Education (CBE): An educational model where progression depends on demonstrating mastery of specific competencies, not on time spent in instruction.",
      "isTrue": true,
      "why": "Competency-based education makes progression depend on demonstrating mastery of specific competencies rather than on time served in instruction. Mastery learning is the classroom practice it generalizes: a threshold before advancing.",
      "derivedFrom": "lt-def-cbe",
      "uid": "1oqpba49tw378"
    },
    {
      "id": "tf-d-learning-theory-lt-def-pck",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "statement": "Pedagogical Content Knowledge (PCK): Shulman's 1986 concept: the specific knowledge teachers need about how to teach a particular subject, distinct from knowing the subject matter itself.",
      "isTrue": true,
      "why": "Pedagogical content knowledge is Shulman's 1986 concept: what teachers need to know about teaching a particular subject, distinct from knowing the subject. Bloom's taxonomy is a different teacher's tool, a ladder of cognitive levels.",
      "derivedFrom": "lt-def-pck",
      "uid": "10zylis1p1izg"
    },
    {
      "id": "tf-df-learning-theory-lt-def-transfer",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "statement": "Multimodal Learning: Applying knowledge or skills learned in one context to new, different contexts.",
      "isTrue": false,
      "why": "Transfer of learning is applying knowledge from one context to a new and different one — the ultimate goal of deep learning, and what shallow memorization fails at. Multimodal learning is about engaging several sensory channels at once.",
      "derivedFrom": "lt-def-transfer",
      "uid": "1bcux68ld4l7k"
    },
    {
      "id": "tf-df-learning-theory-lt-def-working-memory",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "statement": "Chunking: The cognitive system that temporarily holds and manipulates information during active processing (about 7±2 items).",
      "isTrue": false,
      "why": "Working memory is the system that briefly holds and manipulates information during active processing, around seven items at a time. Chunking is the countermeasure: breaking material into smaller units so more fits inside that limit.",
      "derivedFrom": "lt-def-working-memory",
      "uid": "1gangkq12gmti"
    },
    {
      "id": "tf-df-learning-theory-lt-def-chunking",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "pedagogy"
      ],
      "statement": "Working Memory: Breaking complex information into smaller, more manageable units to reduce cognitive load and improve encoding.",
      "isTrue": false,
      "why": "Chunking breaks complex information into smaller, more manageable units to cut cognitive load and improve encoding. Working memory is the constraint that makes it necessary: a store of roughly seven items during active processing.",
      "derivedFrom": "lt-def-chunking",
      "uid": "awidvx183mf7z"
    },
    {
      "id": "tf-d-learning-theory-lt-def-formative-assessment",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "statement": "Formative Assessment: Assessment during the learning process to provide feedback and adjust instruction.",
      "isTrue": true,
      "why": "Formative assessment happens during learning, to give feedback and adjust instruction; a low-stakes quiz that triggers retrieval practice is the classic case. Summative assessment comes after, to grade the outcome.",
      "derivedFrom": "lt-def-formative-assessment",
      "uid": "r7eimm17ep72y"
    },
    {
      "id": "tf-d-learning-theory-lt-def-summative-assessment",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "statement": "Summative Assessment: Evaluation of learning after instruction — exams, final projects — to grade outcomes.",
      "isTrue": true,
      "why": "Summative assessment evaluates learning after instruction — exams, final projects — in order to grade the outcome. Formative assessment runs during instead, feeding back into teaching while there is still time to change it.",
      "derivedFrom": "lt-def-summative-assessment",
      "uid": "wdh7wie3dp1y"
    },
    {
      "id": "tf-d-learning-theory-lt-def-learner-analytics",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "statement": "Learner Analytics: The measurement, collection, analysis, and reporting of data about learners and their contexts in order to optimize learning.",
      "isTrue": true,
      "why": "Learner analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, in order to optimize learning. The Kirkpatrick Model is a narrower frame: Reaction, Learning, Behavior, Results.",
      "derivedFrom": "lt-def-learner-analytics",
      "uid": "3l7fdy1bjrf3u"
    },
    {
      "id": "tf-df-learning-theory-lt-def-kirkpatrick",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "statement": "Learner Analytics: A four-level framework for evaluating training effectiveness: Reaction, then Learning, then Behavior, then Results.",
      "isTrue": false,
      "why": "The Kirkpatrick Model is the four-level framework for evaluating training: Reaction, then Learning, then Behavior, then Results. Learner analytics is broader — collecting and reporting data on learners and contexts to optimize learning.",
      "derivedFrom": "lt-def-kirkpatrick",
      "uid": "13ws2m419nn8fg"
    },
    {
      "id": "tf-d-learning-theory-lt-def-xapi",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "statement": "xAPI / Tin Can API: A learning-data interoperability standard that captures experience statements across all learning contexts, not just the LMS.",
      "isTrue": true,
      "why": "xAPI, also called Tin Can, is the interoperability standard capturing experience statements from every learning context, not just the LMS. SCORM is the older standard it succeeds, which recorded completions and scores only.",
      "derivedFrom": "lt-def-xapi",
      "uid": "1ma81j8cv3mqc"
    },
    {
      "id": "tf-d-learning-theory-lt-def-mooc",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "statement": "MOOC (Massive Open Online Course): A large-scale online course open to unlimited participation.",
      "isTrue": true,
      "why": "A MOOC is a large-scale online course open to unlimited participation, a model Coursera, edX and Udemy pioneered. A syllabus or curriculum map is a different artefact: the outline of objectives, content, sequence and timeline.",
      "derivedFrom": "lt-def-mooc",
      "uid": "jiog4w1px3cw0"
    },
    {
      "id": "tf-d-learning-theory-lt-def-stem-steam",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "statement": "STEM / STEAM: Science, Technology, Engineering, (Arts), and Mathematics — disciplinary categories commonly addressed by edtech platforms.",
      "isTrue": true,
      "why": "STEM and STEAM name the disciplinary categories — Science, Technology, Engineering, Arts and Mathematics — that edtech platforms most often address. EdTech is the broader label: any technology used to help people learn.",
      "derivedFrom": "lt-def-stem-steam",
      "uid": "6050fwv21tno"
    },
    {
      "id": "tf-df-learning-theory-lt-def-edtech",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "statement": "Summative Assessment: Education technology — any technology used to facilitate or enhance learning.",
      "isTrue": false,
      "why": "EdTech is the catch-all term: any technology used to facilitate or enhance learning. Summative assessment is a much narrower thing — evaluation after instruction, exams and final projects, to grade the outcome.",
      "derivedFrom": "lt-def-edtech",
      "uid": "1tzd9ss1lx2jz8"
    },
    {
      "id": "tf-df-learning-theory-lt-def-sdt",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "statement": "MOOC (Massive Open Online Course): Deci & Ryan's theory (1985) naming three basic psychological needs for intrinsic motivation: autonomy, competence, and relatedness.",
      "isTrue": false,
      "why": "Self-Determination Theory is Deci and Ryan's 1985 account of the three needs behind intrinsic motivation: autonomy, competence, relatedness. A MOOC is a delivery format instead — a large-scale online course open to all comers.",
      "derivedFrom": "lt-def-sdt",
      "uid": "hwfax11qoenw7"
    },
    {
      "id": "tf-df-learning-theory-lt-def-syllabus",
      "shape": "trueFalse",
      "tags": [
        "vocabulary",
        "assessment-data"
      ],
      "statement": "MOOC (Massive Open Online Course): A structured outline of learning objectives, content, sequence, and timeline for a course.",
      "isTrue": false,
      "why": "A syllabus or curriculum map is the structured outline of objectives, content, sequence and timeline for a course. A MOOC is the course itself at scale: open online, unlimited participation, pioneered by Coursera, edX and Udemy.",
      "derivedFrom": "lt-def-syllabus",
      "uid": "sz80edow64xb"
    },
    {
      "id": "tf-df-learning-theory-lt-def-operant-conditioning",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "behaviorism",
        "vocabulary"
      ],
      "statement": "Accommodation: Skinner's principle that behavior is shaped by its consequences — reinforcement and punishment — rather than by internal mental states.",
      "isTrue": false,
      "why": "Operant conditioning is Skinner's principle that behaviour is shaped by consequences — reinforcement and punishment — not by internal mental states. Accommodation is Piaget's term: modifying a schema to take in contradictory information.",
      "derivedFrom": "lt-def-operant-conditioning",
      "uid": "1msqnjmtj3yme"
    },
    {
      "id": "tf-df-learning-theory-lt-def-schema",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "statement": "Operant conditioning: A cognitive framework or category used to organize and interpret information.",
      "isTrue": false,
      "why": "A schema is a cognitive framework or category used to organize and interpret information. Operant conditioning is behaviourist rather than cognitive: Skinner's principle that consequences, not internal structures, shape what people do.",
      "derivedFrom": "lt-def-schema",
      "uid": "1uo3xgrb20hk9"
    },
    {
      "id": "tf-df-learning-theory-lt-def-assimilation",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "statement": "Accommodation: Integrating new information into an existing schema without changing the schema itself.",
      "isTrue": false,
      "why": "Assimilation integrates new information into an existing schema, leaving the schema unchanged. Accommodation is the harder move Piaget paired with it: changing the schema itself when new information will not fit.",
      "derivedFrom": "lt-def-assimilation",
      "uid": "krroxp1io4v7j"
    },
    {
      "id": "tf-d-learning-theory-lt-def-accommodation",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "statement": "Accommodation: Modifying an existing schema to incorporate contradictory new information.",
      "isTrue": true,
      "why": "Accommodation is Piaget's term for modifying an existing schema to take in contradictory new information. Assimilation is its partner and the easier of the two: fitting new information into the schema you already had.",
      "derivedFrom": "lt-def-accommodation",
      "uid": "mil12uktjkfu"
    },
    {
      "id": "tf-d-learning-theory-lt-def-equilibration",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "cognitivism",
        "vocabulary"
      ],
      "statement": "Equilibration: The drive to balance assimilation and accommodation, resolving the tension between old schemas and new information.",
      "isTrue": true,
      "why": "Equilibration is the drive to balance assimilation and accommodation, resolving the tension between old schemas and new information. Accommodation is the half that gives ground: the schema itself changes to fit the evidence.",
      "derivedFrom": "lt-def-equilibration",
      "uid": "ti6a731nn2r79"
    },
    {
      "id": "tf-d-learning-theory-lt-def-zpd",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "constructivism",
        "vocabulary"
      ],
      "statement": "Zone of Proximal Development (ZPD): Vygotsky's gap between what a learner can do independently and what they can achieve with guidance from a 'more knowledgeable other'.",
      "isTrue": true,
      "why": "The Zone of Proximal Development is Vygotsky's gap between what a learner can do alone and what they can do with a more knowledgeable other. Scaffolding is the support that carries them across it, then withdraws.",
      "derivedFrom": "lt-def-zpd",
      "uid": "1asriug1sx2y8"
    },
    {
      "id": "tf-d-learning-theory-lt-def-scaffolding",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "constructivism",
        "vocabulary"
      ],
      "statement": "Scaffolding: Temporary instructional support — hints, prompts, models, worked examples — that helps a learner progress through their ZPD, withdrawn as competence grows.",
      "isTrue": true,
      "why": "Scaffolding is temporary instructional support — hints, prompts, models, worked examples — withdrawn as competence grows. The Zone of Proximal Development is the territory it operates in: reachable with help, not yet reachable alone.",
      "derivedFrom": "lt-def-scaffolding",
      "uid": "xeeanaymle7m"
    },
    {
      "id": "tf-d-learning-theory-lt-def-blooms-taxonomy",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "blooms-taxonomy"
      ],
      "statement": "Bloom's Taxonomy: A hierarchy of six cognitive skill levels, from lower-order to higher-order: in the revised version, Remember, Understand, Apply, Analyze, Evaluate, Create.",
      "isTrue": true,
      "why": "Bloom's taxonomy is the hierarchy of six cognitive levels, in the revised version Remember, Understand, Apply, Analyze, Evaluate, Create. The 2 Sigma Problem is Bloom's other famous contribution, about tutoring rather than levels.",
      "derivedFrom": "lt-def-blooms-taxonomy",
      "uid": "ep34e915dbd2z"
    },
    {
      "id": "tf-d-learning-theory-lt-def-two-sigma-problem",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "two-sigma"
      ],
      "statement": "The 2 Sigma Problem: Bloom's 1984 challenge: one-to-one mastery tutoring lifts achievement by about two standard deviations, but is too costly to scale — so find a group method that matches it.",
      "isTrue": true,
      "why": "The 2 Sigma Problem is Bloom's 1984 challenge: one-to-one mastery tutoring lifts achievement about two standard deviations but costs too much to scale, so find a group method that matches it. Mastery learning is one attempt at it.",
      "derivedFrom": "lt-def-two-sigma-problem",
      "uid": "3aum0pdlr4zn"
    },
    {
      "id": "tf-d-learning-theory-lt-def-mastery-learning",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "two-sigma",
        "mastery-learning"
      ],
      "statement": "Mastery learning: An approach where students must reach a threshold (e.g.",
      "isTrue": true,
      "why": "Mastery learning requires students to reach a threshold — say 90% — before advancing, treating failures as instructional gaps rather than student deficits. Competency-based education generalizes it beyond the single classroom.",
      "derivedFrom": "lt-def-mastery-learning",
      "uid": "85qh08mhg6uw"
    },
    {
      "id": "tf-d-learning-theory-lt-def-flow",
      "shape": "trueFalse",
      "tags": [
        "learning-science",
        "flow",
        "motivation"
      ],
      "statement": "Flow: An optimal experience of complete psychological immersion in a task, marked by intense enjoyment and effortless concentration.",
      "isTrue": true,
      "why": "Flow is complete psychological immersion in a task, marked by intense enjoyment and effortless concentration. An autotelic activity is the eighth hallmark of it: something done for its own sake rather than for an external payoff.",
      "derivedFrom": "lt-def-flow",
      "uid": "usu26c1869n64"
    },
    {
      "id": "tf-d-learning-theory-lt-def-autotelic",
      "shape": "trueFalse",
      "tags": [
        "learning-science",
        "flow",
        "motivation"
      ],
      "statement": "Autotelic activity: An activity that is intrinsically rewarding — done for its own sake, not for an external payoff.",
      "isTrue": true,
      "why": "An autotelic activity is intrinsically rewarding, done for its own sake and not for an external payoff — the eighth hallmark of flow. Hebbian learning is a neural principle, unrelated: neurons that fire together wire together.",
      "derivedFrom": "lt-def-autotelic",
      "uid": "1o30lwfa6825x"
    },
    {
      "id": "tf-df-learning-theory-lt-def-dual-coding",
      "shape": "trueFalse",
      "tags": [
        "learning-science",
        "dual-coding",
        "memory"
      ],
      "statement": "Extraneous load: Paivio's idea that humans have two interconnected memory systems — verbal and visual — and learning improves when both are engaged at once.",
      "isTrue": false,
      "why": "Dual Coding Theory is Paivio's idea that verbal and visual memory systems are separate but linked, so learning improves when both are engaged. Extraneous load is a cognitive load category: the unnecessary difficulty bad design adds.",
      "derivedFrom": "lt-def-dual-coding",
      "uid": "13wgydpgz4y3j"
    },
    {
      "id": "tf-df-learning-theory-lt-def-cognitive-load",
      "shape": "trueFalse",
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "statement": "Extraneous load: Sweller's theory (1988) that working memory has limited capacity, so instruction must manage how much mental load the material imposes.",
      "isTrue": false,
      "why": "Cognitive Load Theory is Sweller's 1988 account of working memory's limited capacity and what instruction must do about it. Extraneous load is one of the three loads inside that theory: the waste created by poor design.",
      "derivedFrom": "lt-def-cognitive-load",
      "uid": "32o6th12h6aev"
    },
    {
      "id": "tf-d-learning-theory-lt-def-intrinsic-load",
      "shape": "trueFalse",
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "statement": "Intrinsic load: The cognitive load that comes from the inherent complexity of the material itself — unavoidable, and set by the topic.",
      "isTrue": true,
      "why": "Intrinsic load is the difficulty inherent in the material itself — unavoidable, and set by the topic rather than the teacher. Extraneous load is the avoidable kind, manufactured by poor instructional design.",
      "derivedFrom": "lt-def-intrinsic-load",
      "uid": "yjfcqp1f1nbez"
    },
    {
      "id": "tf-df-learning-theory-lt-def-extraneous-load",
      "shape": "trueFalse",
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "statement": "Germane load: Cognitive load created by poor instructional design — unnecessary complexity that should be eliminated.",
      "isTrue": false,
      "why": "Extraneous load is the cognitive load created by poor instructional design — unnecessary complexity that should simply be removed. Germane load is the productive kind: effort going into building mental schemas, which designers maximize.",
      "derivedFrom": "lt-def-extraneous-load",
      "uid": "t37z2m1tdkgz6"
    },
    {
      "id": "tf-d-learning-theory-lt-def-germane-load",
      "shape": "trueFalse",
      "tags": [
        "learning-science",
        "cognitive-load",
        "memory"
      ],
      "statement": "Germane load: Cognitive effort directed at building mental schemas — the productive load that designers should maximize.",
      "isTrue": true,
      "why": "Germane load is cognitive effort spent building mental schemas — the productive load a designer should maximize. Extraneous load is its opposite number, the unnecessary difficulty poor design adds and that should be stripped out.",
      "derivedFrom": "lt-def-germane-load",
      "uid": "tk6oka1qmpjla"
    },
    {
      "id": "tf-d-learning-theory-lt-def-connectivism",
      "shape": "trueFalse",
      "tags": [
        "theory",
        "connectivism",
        "digital-age"
      ],
      "statement": "Connectivism: Siemens and Downes's 'learning theory for the digital age': learning is the process of creating connections between nodes in a network.",
      "isTrue": true,
      "why": "Connectivism is Siemens and Downes's learning theory for the digital age: learning as the process of creating connections between nodes in a network. Constructivism, the tradition before it, put the individual mind at the centre.",
      "derivedFrom": "lt-def-connectivism",
      "uid": "jbjva61qyrnfe"
    },
    {
      "id": "tf-df-learning-theory-lt-def-udl",
      "shape": "trueFalse",
      "tags": [
        "instructional-design",
        "udl",
        "accessibility"
      ],
      "statement": "The Socratic method: A neuroscience-based curriculum framework (Rose, CAST) that builds flexibility into learning from the outset rather than adding accommodations afterward.",
      "isTrue": false,
      "why": "Universal Design for Learning is Rose and CAST's framework, building flexibility into curriculum from the outset instead of bolting accommodations on afterwards. The Socratic method is a teaching move: guided questions, not direct answers.",
      "derivedFrom": "lt-def-udl",
      "uid": "povnox1xc6rkj"
    },
    {
      "id": "tf-df-learning-theory-lt-def-method-of-loci",
      "shape": "trueFalse",
      "tags": [
        "memory",
        "mnemonics",
        "method-of-loci"
      ],
      "statement": "Keyword Method: An ancient technique that places items to be memorized at spatial locations along a familiar mental journey; walking the path retrieves them in sequence.",
      "isTrue": false,
      "why": "The Method of Loci places items at spatial points along a familiar mental journey, so walking the path retrieves them in sequence. The Keyword Method is the language mnemonic instead: a foreign word's sound hooked to a bridging image.",
      "derivedFrom": "lt-def-method-of-loci",
      "uid": "9yjcda1ckq10q"
    },
    {
      "id": "tf-df-learning-theory-lt-def-keyword-method",
      "shape": "trueFalse",
      "tags": [
        "memory",
        "mnemonics",
        "keyword-method"
      ],
      "statement": "Method of Loci (Memory Palace): A language-learning mnemonic that links a foreign word's sound to a memorable image which bridges to the translation.",
      "isTrue": false,
      "why": "The Keyword Method links a foreign word's sound to a memorable image that bridges to the translation. The Method of Loci is the older spatial technique: items placed along a familiar route and collected by walking it.",
      "derivedFrom": "lt-def-keyword-method",
      "uid": "1koqlzeroyqny"
    },
    {
      "id": "tf-df-learning-theory-lt-def-addie",
      "shape": "trueFalse",
      "tags": [
        "instructional-design",
        "addie"
      ],
      "statement": "The Socratic method: An instructional systems design framework structured as five phases: Analyze, Design, Develop, Implement, and Evaluate.",
      "isTrue": false,
      "why": "ADDIE is the instructional systems design framework of five phases — Analyze, Design, Develop, Implement, Evaluate. The Socratic method is not a design process at all: teaching by guided, probing questions rather than direct answers.",
      "derivedFrom": "lt-def-addie",
      "uid": "vsgmqj1y5h3lt"
    },
    {
      "id": "tf-d-learning-theory-lt-def-backward-design",
      "shape": "trueFalse",
      "tags": [
        "instructional-design",
        "frameworks"
      ],
      "statement": "Backward design: Wiggins and McTighe's approach in Understanding by Design: start from the desired learning outcomes, then work back to assessments and instruction.",
      "isTrue": true,
      "why": "Backward design is Wiggins and McTighe's approach in Understanding by Design: start from the desired outcomes, then work back to assessments and instruction. Action Mapping is Cathy Moore's cousin, built around what learners must do.",
      "derivedFrom": "lt-def-backward-design",
      "uid": "yvh50y1x4cgt2"
    },
    {
      "id": "tf-df-learning-theory-lt-def-action-mapping",
      "shape": "trueFalse",
      "tags": [
        "instructional-design",
        "frameworks"
      ],
      "statement": "Backward design: Cathy Moore's 2008 performance-focused method that strips out 'nice to know' content and designs around what learners must actually do.",
      "isTrue": false,
      "why": "Action Mapping is Cathy Moore's 2008 performance-focused method, stripping out 'nice to know' content and designing around what learners must actually do. Backward design starts from desired outcomes and works back to assessment.",
      "derivedFrom": "lt-def-action-mapping",
      "uid": "1i3wybb11kbbj1"
    },
    {
      "id": "tf-d-learning-theory-lt-def-socratic-method",
      "shape": "trueFalse",
      "tags": [
        "instructional-design",
        "socratic"
      ],
      "statement": "The Socratic method: Teaching through guided, probing questions rather than direct answers, so the learner constructs the insight independently — yielding deeper encoding.",
      "isTrue": true,
      "why": "The Socratic method teaches through guided, probing questions rather than direct answers, so the learner constructs the insight and encodes it deeply. Khanmigo is built on it, guiding step by step and never handing over the answer.",
      "derivedFrom": "lt-def-socratic-method",
      "uid": "cqoyo71q6hq4d"
    },
    {
      "id": "tf-d-learning-theory-lt-def-personalization-problem",
      "shape": "trueFalse",
      "tags": [
        "edtech",
        "brave-new-words",
        "personalization"
      ],
      "statement": "The personalization problem: Great education requires understanding where a specific learner is, what they know, how they learn, and what engages them — historically only possible with expensive private tutors.",
      "isTrue": true,
      "why": "The personalization problem is that good teaching needs to know where a learner is, what they know and what engages them — historically affordable only with a private tutor. The 2 Sigma Problem is the measured version of that gap.",
      "derivedFrom": "lt-def-personalization-problem",
      "uid": "5wguh4162gmm8"
    },
    {
      "id": "tf-d-learning-theory-lt-def-khanmigo",
      "shape": "trueFalse",
      "tags": [
        "edtech",
        "khanmigo",
        "ai"
      ],
      "statement": "Khanmigo: An AI tutoring assistant built on GPT-4 in collaboration with OpenAI.",
      "isTrue": true,
      "why": "Khanmigo is the AI tutoring assistant built on GPT-4 with OpenAI, its name playing on 'Khan' and the Spanish conmigo, 'with me'. It works by the Socratic method, guiding step by step and never simply delivering the answer.",
      "derivedFrom": "lt-def-khanmigo",
      "uid": "1aly3w31m1cc7l"
    },
    {
      "id": "tf-df-learning-theory-lt-def-adaptive-learning",
      "shape": "trueFalse",
      "tags": [
        "platforms",
        "vocabulary"
      ],
      "statement": "Problem-Based Learning (PBL): Software that adjusts the content, sequence, and difficulty of instruction in real time based on each learner's performance history.",
      "isTrue": false,
      "why": "An adaptive learning system adjusts content, sequence and difficulty in real time from each learner's performance history. Problem-based learning is a human pedagogy instead: students learn by investigating an authentic, open-ended problem.",
      "derivedFrom": "lt-def-adaptive-learning",
      "uid": "1larxok1va7tf0"
    },
    {
      "id": "tf-d-learning-theory-lt-def-intelligent-tutoring",
      "shape": "trueFalse",
      "tags": [
        "evidence",
        "vocabulary"
      ],
      "statement": "Intelligent tutoring system: A computer system that delivers individualized instruction and feedback, modeling both the subject and the learner's evolving understanding to guide them like a one-on-one tutor.",
      "isTrue": true,
      "why": "An intelligent tutoring system delivers individualized instruction and feedback, modelling both the subject and the learner's evolving understanding to guide them like a one-to-one tutor. An adaptive system only tunes difficulty and order.",
      "derivedFrom": "lt-def-intelligent-tutoring",
      "uid": "uj2tuo18axgt4"
    },
    {
      "id": "tf-d-learning-theory-lt-def-scorm",
      "shape": "trueFalse",
      "tags": [
        "standards",
        "lms",
        "vocabulary"
      ],
      "statement": "SCORM: Sharable Content Object Reference Model (2001) — the original interoperability standard letting content work across different LMSs.",
      "isTrue": true,
      "why": "SCORM, the Sharable Content Object Reference Model of 2001, was the original standard letting content run across different LMSs; it tracks completions and quiz scores only. An LRS stores the finer xAPI record of what actually happened.",
      "derivedFrom": "lt-def-scorm",
      "uid": "irmbjolr5uf8"
    },
    {
      "id": "tf-df-learning-theory-lt-def-lrs",
      "shape": "trueFalse",
      "tags": [
        "standards",
        "lms",
        "vocabulary"
      ],
      "statement": "SCORM: The backend database that stores xAPI statements — a portable, durable repository of all learning activity across systems.",
      "isTrue": false,
      "why": "An LRS is the backend database holding xAPI statements — a portable, durable record of learning activity across systems. SCORM is the 2001 interoperability standard that came first, and it tracks completions and quiz scores only.",
      "derivedFrom": "lt-def-lrs",
      "uid": "17n7ny819bttsg"
    },
    {
      "id": "tf-df-learning-theory-lt-def-gamification",
      "shape": "trueFalse",
      "tags": [
        "gamification",
        "vocabulary"
      ],
      "statement": "Accommodation: The application of game design elements — points, badges, leaderboards, levels, narrative, challenges — to non-game contexts to increase engagement and motivation.",
      "isTrue": false,
      "why": "Gamification applies game design elements — points, badges, leaderboards, levels, narrative — to non-game contexts to lift engagement; Nick Pelling coined the term in 2003. Accommodation is Piaget's: reshaping a schema to fit new information.",
      "derivedFrom": "lt-def-gamification",
      "uid": "f74mjl1tpy5t7"
    },
    {
      "id": "concept-rw-learning-theory-the-diamond-age",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "fiction",
        "equity"
      ],
      "name": "The Diamond Age",
      "clues": [
        "One of three works of speculative fiction Khan credits with shaping his vision of personalized instruction for any child.",
        "In its story, an AI tutor transforms the life of a poor girl."
      ],
      "uid": "154kunzuxpr1h"
    },
    {
      "id": "concept-rw-learning-theory-ender-s-game",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "fiction",
        "simulation"
      ],
      "name": "Ender's Game",
      "clues": [
        "One of three speculative-fiction works Khan names as inspiration for his 2024 book on AI and learning.",
        "He cites it for its vision of challenge-driven simulation learning, where students grow through immersive trials."
      ],
      "uid": "13h3fxgvnpyuc"
    },
    {
      "id": "concept-rw-learning-theory-the-fun-they-had",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "fiction",
        "asimov"
      ],
      "name": "The Fun They Had",
      "clues": [
        "An Isaac Asimov short story Khan lists among the fiction that shaped his vision of universal tutoring.",
        "In it, a future child finds a classroom full of human peers exotic and strange."
      ],
      "uid": "a1yc8r1ivslnd"
    },
    {
      "id": "concept-rw-learning-theory-khanmigo",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "ai-tutor",
        "platform"
      ],
      "name": "Khanmigo",
      "clues": [
        "An AI tutor deliberately built to refuse direct answers, instead responding with guiding questions that push students to construct understanding.",
        "Powered by GPT-4, it is integrated with a full K-12 content library spanning math, humanities, coding, and social studies.",
        "Positioned as a teacher assistant, not a replacement, by 2024–25 it was serving 700,000 K-12 students."
      ],
      "uid": "k939rz1yj436d"
    },
    {
      "id": "concept-rw-learning-theory-duolingo",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "language-learning",
        "platform"
      ],
      "name": "Duolingo",
      "clues": [
        "A popular language-learning app whose proprietary adaptive model orchestrates the entire lesson experience.",
        "That adaptive engine is called BirdBrain; a GPT-4-powered premium tier adds roleplay and an 'Explain My Answer' feature.",
        "Its premium tier, Max, includes a 'Lily' chat mode for open-ended conversation practice."
      ],
      "uid": "qzkzjnxqhqnl"
    },
    {
      "id": "concept-rw-learning-theory-magicschool-ai",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "teacher-tools",
        "platform"
      ],
      "name": "MagicSchool AI",
      "clues": [
        "A teacher-tools platform for lesson planning, rubric generation, and cutting administrative work, keeping the educator central.",
        "It reached over 2 million educators and 4,000+ institutions within its first year — fast adoption by edtech standards.",
        "A $45M Series B in 2025 funds its shift from a loose collection of tools into a connected teaching system, winning procurement via safety and district-policy alignment."
      ],
      "uid": "wkbe7565qwvv"
    },
    {
      "id": "concept-rw-learning-theory-synthesis",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "math",
        "platform"
      ],
      "name": "Synthesis",
      "clues": [
        "An adaptive K-6 math platform with a voice-guided interface that favors conceptual understanding over rote drilling.",
        "Founded by Chrisman Frank, it was originally built for the SpaceX employee school.",
        "A ~$99/year family subscription; by 2025 it was on pace for $10M+ revenue, with subscribed students up 4.5x year-over-year."
      ],
      "uid": "1wpnqj1vvccop"
    },
    {
      "id": "concept-rw-learning-theory-google-notebooklm",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "research-assistant",
        "platform"
      ],
      "name": "Google NotebookLM",
      "clues": [
        "The canonical example of the 'Research Assistants' category in the AI-in-education taxonomy.",
        "It ingests documents — PDFs, YouTube videos, web pages — to build a source-grounded knowledge base you can query.",
        "Because its answers stay grounded in your provided sources, builders use it to spin up custom learning assistants without fine-tuning; outputs include audio podcasts and slide outlines."
      ],
      "uid": "1696v6zw0vmht"
    },
    {
      "id": "concept-rw-learning-theory-plato",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "lms",
        "history"
      ],
      "name": "PLATO",
      "clues": [
        "Launched in 1960 at the University of Illinois, a mainframe system that anticipated modern e-learning by roughly thirty years.",
        "Created by Donald Bitzer, it supported simultaneous users, touchscreen interaction, and early online community.",
        "Its name is an acronym: Programmed Logic for Automated Teaching Operations."
      ],
      "uid": "10tzlre871zgu"
    },
    {
      "id": "concept-rw-learning-theory-moodle",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "lms",
        "open-source"
      ],
      "name": "Moodle",
      "clues": [
        "Released in 2002 as open-source software, it shifted power toward institutions unwilling to pay enterprise licensing fees.",
        "Created by Martin Dougiamas, its constructivist design philosophy and zero cost drove wide adoption.",
        "It became the dominant learning management system in international higher education."
      ],
      "uid": "5x7z6u7l9qxe"
    },
    {
      "id": "concept-rw-learning-theory-canvas",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "lms",
        "saas"
      ],
      "name": "Canvas",
      "clues": [
        "A cloud- and SaaS-era learning platform noted for its clean, instruction-friendly interface.",
        "Made by Instructure, it steadily gained market share during the 2010s consolidation.",
        "It won share from a long-entrenched incumbent whose clunky UX and aggressive pricing left openings."
      ],
      "uid": "1okfyok1t5sh5g"
    },
    {
      "id": "concept-rw-learning-theory-blackboard",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "lms",
        "history"
      ],
      "name": "Blackboard",
      "clues": [
        "For years the long-entrenched, dominant learning management system before cloud-era rivals emerged.",
        "Its reputation for clunky UX and aggressive pricing created openings for nimbler competitors.",
        "During the 2010s it steadily lost market share to Instructure's cleaner, instruction-friendly platform."
      ],
      "uid": "1a2q37315qqujx"
    },
    {
      "id": "concept-rw-learning-theory-cognitive-tutor",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "intelligent-tutoring",
        "adaptive"
      ],
      "name": "Cognitive Tutor",
      "clues": [
        "The canonical, textbook example of an AI system that instructs a student one-on-one without any human teacher.",
        "Developed at Carnegie Mellon, it models how a student thinks and delivers personalized hints and feedback within a specific domain, originally mathematics."
      ],
      "uid": "rhi32y12wtazy"
    },
    {
      "id": "concept-rw-learning-theory-bayesian-knowledge-tracing",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "knowledge-tracing",
        "adaptive"
      ],
      "name": "Bayesian Knowledge Tracing",
      "clues": [
        "One of two competing methods for estimating what a specific learner currently knows, updating after every response.",
        "It is a probabilistic model that computes the probability a learner has mastered a skill, relying on hand-crafted probability tables."
      ],
      "uid": "p3vxa1pqgomy"
    },
    {
      "id": "concept-rw-learning-theory-deep-knowledge-tracing",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "knowledge-tracing",
        "adaptive"
      ],
      "name": "Deep Knowledge Tracing",
      "clues": [
        "The newer of two competing methods for estimating a learner's evolving mastery after each interaction.",
        "It replaces hand-crafted probability tables with a recurrent neural network (an LSTM) that models a learner's mastery as an evolving hidden state (Piech et al., 2015)."
      ],
      "uid": "d18psn7maet9"
    },
    {
      "id": "concept-rw-learning-theory-knowledge-state",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "adaptive-systems",
        "modeling"
      ],
      "name": "Knowledge State",
      "clues": [
        "A continuously updated model, at the heart of adaptive software, of what a specific learner does and doesn't understand.",
        "It is precisely the thing two competing methods — one probabilistic, one a neural network — race to estimate."
      ],
      "uid": "ip2jt116ygkbb"
    },
    {
      "id": "concept-rw-learning-theory-passive-learning",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "learning-modes"
      ],
      "name": "Passive learning",
      "clues": [
        "The weakest of the three modes of engagement, it keeps the brain only lightly activated.",
        "Its typical activities are re-reading a chapter or re-watching a lecture.",
        "Because the target neurons never fire during retrieval or use, the synaptic connection barely strengthens."
      ],
      "uid": "hwk22mc4a2gy"
    },
    {
      "id": "concept-rw-learning-theory-active-learning",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "learning-modes"
      ],
      "name": "Active learning",
      "clues": [
        "This mode sits above the weakest one because it demands effortful mental work.",
        "It requires the learner to reconstruct stored information rather than re-expose themselves to it.",
        "By forcing retrieval, it fires the target neurons and begins to wire them together."
      ],
      "uid": "2tlyon1msgb0d"
    },
    {
      "id": "concept-rw-learning-theory-interactive-learning",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "learning-modes"
      ],
      "name": "Interactive learning",
      "clues": [
        "The deepest of the three modes, it produces the most robust encoding.",
        "Its signature activities are teaching others and debating.",
        "It demands 'schema negotiation' — you must integrate, defend, and adapt a fact, not merely recall it."
      ],
      "uid": "1clkvmj1g1sygp"
    },
    {
      "id": "concept-rw-learning-theory-hebbian-learning",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "neuroscience",
        "learning-modes"
      ],
      "name": "Hebbian learning",
      "clues": [
        "This principle works at the cellular level, describing how a skill or memory physically takes hold.",
        "It holds that repeated co-activation thickens the synapse so signals travel faster.",
        "It is famously summed up as 'neurons that fire together, wire together.'"
      ],
      "uid": "uqgxtm1lh0nba"
    },
    {
      "id": "concept-rw-learning-theory-schema",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "cognitivism",
        "piaget"
      ],
      "name": "Schema",
      "clues": [
        "Piaget gave cognitivism its richest vocabulary for knowledge structure, and this is its basic building block.",
        "It is a cognitive framework — a stored pattern of understanding — used to interpret new information.",
        "New information that fits one is absorbed intact; information that clashes forces the learner to revise it."
      ],
      "uid": "i7kk0mddwqmi"
    },
    {
      "id": "concept-rw-learning-theory-assimilation",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "cognitivism",
        "piaget"
      ],
      "name": "Assimilation",
      "clues": [
        "One of Piaget's two complementary processes for fitting new information to an existing mental framework.",
        "It is the easier of the pair: the incoming information already fits, so the framework stays intact.",
        "When new digits slot neatly into a pattern you already hold, that effortless absorption is this process."
      ],
      "uid": "1vmiu86ch6456"
    },
    {
      "id": "concept-rw-learning-theory-accommodation",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "cognitivism",
        "piaget"
      ],
      "name": "Accommodation",
      "clues": [
        "This is the more effortful of Piaget's two adaptation processes.",
        "It kicks in when new information contradicts an existing schema.",
        "The learner must revise the framework itself, producing genuine conceptual change rather than a simple fit."
      ],
      "uid": "cegmnzgwmy39"
    },
    {
      "id": "concept-rw-learning-theory-equilibration",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "cognitivism",
        "piaget"
      ],
      "name": "Equilibration",
      "clues": [
        "Piaget called this the engine of cognitive development.",
        "It is the drive to resolve the tension between an outdated framework and a new, conflicting experience.",
        "This balancing process pushes a learner from mental conflict back toward a stable, updated understanding."
      ],
      "uid": "8a2xc0vwegaw"
    },
    {
      "id": "concept-rw-learning-theory-remember",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "blooms-taxonomy"
      ],
      "name": "Remember",
      "clues": [
        "The lowest rung of Bloom's six-level cognitive hierarchy.",
        "It represents lower-order thinking — the simple recall of information.",
        "In the 1956 original this bottom level was called 'Knowledge'; the 2001 revision renamed it with an action verb."
      ],
      "uid": "ut7arwqfudvg"
    },
    {
      "id": "concept-rw-learning-theory-evaluate",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "blooms-taxonomy"
      ],
      "name": "Evaluate",
      "clues": [
        "This is one of the two highest levels in Bloom's revised taxonomy.",
        "It concerns complex judgment, near the summit of higher-order thinking.",
        "In the 2001 revision it was knocked down one rung, surrendering the top spot to the level about creating."
      ],
      "uid": "1pn91wa1238uim"
    },
    {
      "id": "concept-rw-learning-theory-create",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "blooms-taxonomy"
      ],
      "name": "Create",
      "clues": [
        "This occupies the very summit of Bloom's revised taxonomy.",
        "It sits at the top of higher-order thinking, above the level concerned with judgment.",
        "In the 1956 original it was called 'Synthesis'; the 2001 revision renamed it and promoted it to the peak."
      ],
      "uid": "14aznhx1k9n1xz"
    },
    {
      "id": "concept-rw-learning-theory-allan-paivio",
      "shape": "concept",
      "conceptKind": "person",
      "tags": [
        "person",
        "dual-coding",
        "theorist"
      ],
      "name": "Allan Paivio",
      "clues": [
        "This researcher's 1971 theory explains why a diagram paired with an explanation beats a wall of text.",
        "He proposed that humans run two interconnected memory systems — one verbal, one visual.",
        "His dual-coding model says engaging both channels at once improves learning; mnemonic images exploit it."
      ],
      "uid": "1v215paxkei1m"
    },
    {
      "id": "concept-rw-learning-theory-stephen-downes",
      "shape": "concept",
      "conceptKind": "person",
      "tags": [
        "person",
        "connectivism",
        "theorist"
      ],
      "name": "Stephen Downes",
      "clues": [
        "This thinker co-created a framework billed as 'the learning theory for the digital age.'",
        "Working with a collaborator in 2004-05, he cast learning as forming connections between nodes in a network.",
        "His theory prized 'know-where' — locating and evaluating information — over memorizing content a search away."
      ],
      "uid": "1ps1p3ft6o1b5"
    },
    {
      "id": "concept-rw-learning-theory-robert-gagn",
      "shape": "concept",
      "conceptKind": "person",
      "tags": [
        "person",
        "instructional-design",
        "theorist"
      ],
      "name": "Robert Gagné",
      "clues": [
        "This theorist's 1965 book argued that different learning outcomes each need a different teaching approach.",
        "He named five outcome categories — verbal information, intellectual skills, cognitive strategies, motor skills, and attitudes.",
        "His 'Nine Events of Instruction' start by gaining attention before any content is delivered."
      ],
      "uid": "2yxiczzmaqx5"
    },
    {
      "id": "concept-rw-learning-theory-david-rose",
      "shape": "concept",
      "conceptKind": "person",
      "tags": [
        "person",
        "udl",
        "theorist"
      ],
      "name": "David Rose",
      "clues": [
        "This researcher built a neuroscience-based curriculum framework at an organization called CAST.",
        "His approach designs in flexibility from the outset instead of retrofitting accommodations, treating learner variability as normal.",
        "Universal Design for Learning — Representation, Action & Expression, and Engagement — is his framework."
      ],
      "uid": "9e4x1ryaajvp"
    },
    {
      "id": "concept-rw-learning-theory-sam-successive-approximation-model",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "instructional-design",
        "framework"
      ],
      "name": "SAM (Successive Approximation Model)",
      "clues": [
        "Michael Allen built this framework in 2012 as a direct counterpoint to a decades-old linear model.",
        "It attacks the rigidity of phase-by-phase design by cycling through prototyping and revision far earlier.",
        "Its entire selling point is rapid prototyping and short, repeated feedback loops."
      ],
      "uid": "fzp3h852oj18"
    },
    {
      "id": "concept-rw-learning-theory-dick-carey-model",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "instructional-design",
        "framework"
      ],
      "name": "Dick & Carey Model",
      "clues": [
        "This 1978 framework takes a systems view of instruction.",
        "Rather than sequential phases, it treats instruction as a set of interacting components.",
        "Precisely, it models instruction as nine interacting components working together as a system."
      ],
      "uid": "59fbilwbkvrz"
    },
    {
      "id": "concept-rw-learning-theory-merrill-s-principles-of-instruction",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "instructional-design",
        "framework"
      ],
      "name": "Merrill's Principles of Instruction",
      "clues": [
        "Published in 2002, this framework distills effective teaching into a short set of 'first' fundamentals.",
        "It is task-centered and problem-centered at its core.",
        "Its five pillars: problem-centered, activation, demonstration, application, and integration."
      ],
      "uid": "avaopk12hzosg"
    },
    {
      "id": "concept-rw-learning-theory-understanding-by-design-ubd",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "instructional-design",
        "framework"
      ],
      "name": "Understanding by Design (UbD)",
      "clues": [
        "Wiggins and McTighe introduced this framework in 1998.",
        "Its signature move is 'backward design': begin from the desired learning outcomes.",
        "You work back from target outcomes to assessments, and only then to the instruction itself."
      ],
      "uid": "1gt2vos10hnkfw"
    },
    {
      "id": "concept-rw-learning-theory-action-mapping",
      "shape": "concept",
      "conceptKind": "thing",
      "tags": [
        "thing",
        "instructional-design",
        "framework"
      ],
      "name": "Action Mapping",
      "clues": [
        "Cathy Moore introduced this performance-focused method in 2008.",
        "It ruthlessly strips out 'nice to know' content.",
        "It designs a course entirely around what learners must actually do on the job."
      ],
      "uid": "4xby6bayv59d"
    },
    {
      "id": "ot-hebbian-1",
      "shape": "mcq",
      "tags": [
        "hebbian",
        "neuroscience"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which principle states that synaptic connections between neurons strengthen when those neurons activate together?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Pavlovian conditioning"
        },
        {
          "modality": "text",
          "value": "Hebbian learning"
        },
        {
          "modality": "text",
          "value": "Skinnerian shaping"
        },
        {
          "modality": "text",
          "value": "Piagetian assimilation"
        }
      ],
      "correctIndex": 1,
      "explanation": "Hebbian learning is the principle summarized as 'neurons that fire together, wire together.' Pavlovian conditioning pairs stimuli, Skinnerian shaping rewards successive approximations, and Piagetian assimilation absorbs new information into an existing schema — none describes synaptic co-activation.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "lezru1ljntji"
    },
    {
      "id": "ot-hebbian-2",
      "shape": "mcq",
      "tags": [
        "hebbian",
        "synapse"
      ],
      "prompt": {
        "modality": "text",
        "value": "At the cellular level, what physically changes when repeated co-activation strengthens a learned pattern?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The neuron is replaced and a new one takes over the pattern"
        },
        {
          "modality": "text",
          "value": "The synapse thickens and signals travel faster"
        },
        {
          "modality": "text",
          "value": "The firing threshold rises and signals slow down"
        },
        {
          "modality": "text",
          "value": "The cell body enlarges and holds the pattern itself"
        }
      ],
      "correctIndex": 1,
      "explanation": "The guide states repeated co-activation makes connections structurally stronger — the synapse thickens and signals travel faster. Learning strengthens existing connections rather than growing replacement neurons.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "hrgibgf5ygh8"
    },
    {
      "id": "ot-hebbian-3",
      "shape": "mcq",
      "tags": [
        "passive-learning",
        "hebbian"
      ],
      "prompt": {
        "modality": "text",
        "value": "Why does passive exposure to material rarely produce mastery, according to the Hebbian account?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The neurons encoding it fire too often during exposure, so the synapse fatigues and cannot strengthen",
          "short": "Fire too often, synapse fatigues"
        },
        {
          "modality": "text",
          "value": "The neurons encoding it never fire during retrieval or use, so the connection doesn't strengthen",
          "short": "Neurons never fire, no strengthening"
        },
        {
          "modality": "text",
          "value": "The neurons encoding it fire in the wrong order, so each exposure weakens the connection instead",
          "short": "Wrong order, exposure weakens link"
        },
        {
          "modality": "text",
          "value": "The neurons encoding it fire in isolation, so there is no partner neuron for a synapse to form",
          "short": "Fire alone, no partner to wire with"
        }
      ],
      "correctIndex": 1,
      "explanation": "Passive learning keeps activation low, so the target neurons don't fire in the context of retrieval and the connection never wires. Exposure doesn't erase prior synapses — it simply fails to strengthen new ones.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1ndkryn66u2hx"
    },
    {
      "id": "ot-hebbian-4",
      "shape": "mcq",
      "tags": [
        "hebbian",
        "practice"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which is NOT an accurate statement about practice and repetition in the Hebbian view?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Repeated co-activation makes connections structurally stronger",
          "short": "Repeated co-activation strengthens links"
        },
        {
          "modality": "text",
          "value": "Varied application helps strengthen connections",
          "short": "Varied application strengthens links"
        },
        {
          "modality": "text",
          "value": "Passive learning keeps activation low and connection-building weak",
          "short": "Passive learning keeps activation low"
        },
        {
          "modality": "text",
          "value": "Practice and repetition are merely motivational advice",
          "short": "Practice is merely motivational advice"
        }
      ],
      "correctIndex": 3,
      "explanation": "The guide is explicit that practice, repetition, and varied application are not motivational advice — they are the literal mechanism of biological change. The other three statements all match the guide.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1isau871psqbk5"
    },
    {
      "id": "ot-hebbian-5",
      "shape": "mcq",
      "tags": [
        "hebbian",
        "passive-learning",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "A student re-watches a lecture five times but never quizzes herself. Applying Hebbian learning, what best predicts her outcome?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Strong mastery, because each re-watch fires the encoding neurons again",
          "short": "Strong — each re-watch fires neurons"
        },
        {
          "modality": "text",
          "value": "Weak connection-building, because activation stays low without retrieval",
          "short": "Weak wiring — no retrieval activation"
        },
        {
          "modality": "text",
          "value": "Gradual mastery, because exposure strengthens synapses as reliably as retrieval",
          "short": "Gradual — exposure equals retrieval"
        },
        {
          "modality": "text",
          "value": "No lasting trace, because each re-watch overwrites the previous encoding",
          "short": "No trace — re-watch overwrites it"
        }
      ],
      "correctIndex": 1,
      "explanation": "Re-watching is passive: activation stays low and the neurons never fire in a retrieval context, so wiring is weak. Repetition only builds connections when the target neurons actually fire during recall or use.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "etocmy9nx4fq"
    },
    {
      "id": "ot-modes-1",
      "shape": "mcq",
      "tags": [
        "active-learning",
        "modes"
      ],
      "prompt": {
        "modality": "text",
        "value": "Recalling, practicing, and self-testing are the defining behaviors of which mode of learning?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Passive learning"
        },
        {
          "modality": "text",
          "value": "Interactive learning"
        },
        {
          "modality": "text",
          "value": "Active learning"
        },
        {
          "modality": "text",
          "value": "Exposure learning"
        }
      ],
      "correctIndex": 2,
      "explanation": "Active learning is defined as recalling, practicing, and testing — it reinforces neural pathways. Interactive learning goes further, adding teaching and debating.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "16whg8918o27iz"
    },
    {
      "id": "ot-modes-2",
      "shape": "mcq",
      "tags": [
        "passive-learning",
        "modes"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which activity belongs to passive learning rather than active or interactive learning?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Quizzing yourself with flashcards you wrote"
        },
        {
          "modality": "text",
          "value": "Re-reading a chapter you already highlighted"
        },
        {
          "modality": "text",
          "value": "Teaching the concept to a peer who missed class"
        },
        {
          "modality": "text",
          "value": "Debating a claim with a classmate who disagrees"
        }
      ],
      "correctIndex": 1,
      "explanation": "Passive learning is observing, watching, and reading — re-reading fits squarely. Flashcards are active retrieval; teaching and debating are interactive.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "j12twrads0op"
    },
    {
      "id": "ot-modes-3",
      "shape": "mcq",
      "tags": [
        "modes",
        "ranking"
      ],
      "prompt": {
        "modality": "text",
        "value": "Ranked from weakest to strongest for retention, what is the correct order of the three modes?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Active → passive → interactive"
        },
        {
          "modality": "text",
          "value": "Interactive → active → passive"
        },
        {
          "modality": "text",
          "value": "Passive → active → interactive"
        },
        {
          "modality": "text",
          "value": "Interactive → passive → active"
        }
      ],
      "correctIndex": 2,
      "explanation": "Passive learning is weakest for retention, active learning reinforces neural pathways, and interactive learning demands the deepest retrieval — producing the most robust encoding.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1gfwdtx3b0xsf"
    },
    {
      "id": "ot-modes-4",
      "shape": "mcq",
      "tags": [
        "interactive-learning",
        "schema"
      ],
      "prompt": {
        "modality": "text",
        "value": "What extra demand does interactive learning place on the learner beyond simply recalling a fact?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Dual coding — visualizing, verbalizing, and pairing the fact",
          "short": "Dual coding: picturing the fact"
        },
        {
          "modality": "text",
          "value": "Schema negotiation — integrating, defending, and adapting the fact",
          "short": "Schema negotiation: adapting the fact"
        },
        {
          "modality": "text",
          "value": "Chunking — splitting, grouping, and relabeling the fact",
          "short": "Chunking: regrouping the fact"
        },
        {
          "modality": "text",
          "value": "Spaced repetition — resting, recalling, and re-testing the fact",
          "short": "Spaced repetition: re-testing later"
        }
      ],
      "correctIndex": 1,
      "explanation": "Teaching and debating force schema negotiation: you must not only recall a fact but integrate it, defend it, and adapt it. That layered demand is what produces the most robust encoding.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "ef271joa148d"
    },
    {
      "id": "ot-forget-1",
      "shape": "mcq",
      "tags": [
        "forgetting-curve",
        "numbers"
      ],
      "prompt": {
        "modality": "text",
        "value": "Roughly what share of new information is lost within 30 minutes when it is never reviewed?"
      },
      "options": [
        {
          "modality": "text",
          "value": "25%"
        },
        {
          "modality": "text",
          "value": "50%"
        },
        {
          "modality": "text",
          "value": "90%"
        },
        {
          "modality": "text",
          "value": "75%"
        }
      ],
      "correctIndex": 1,
      "explanation": "Ebbinghaus found about 50% of new information is gone within 30 minutes without review. Roughly 75% is the 24-hour figure, not the 30-minute one.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "z8msyj11vydf5"
    },
    {
      "id": "ot-forget-2",
      "shape": "mcq",
      "tags": [
        "forgetting-curve",
        "numbers"
      ],
      "prompt": {
        "modality": "text",
        "value": "Without any review, approximately how much new information is gone after 24 hours?"
      },
      "options": [
        {
          "modality": "text",
          "value": "About 50%"
        },
        {
          "modality": "text",
          "value": "About 75%"
        },
        {
          "modality": "text",
          "value": "About 95%"
        },
        {
          "modality": "text",
          "value": "About 30%"
        }
      ],
      "correctIndex": 1,
      "explanation": "Ebbinghaus's curve shows roughly 75% lost within 24 hours. About 50% is the 30-minute figure — the decay continues well past the first half hour.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "xk1ao1y1xr23"
    },
    {
      "id": "ot-forget-3",
      "shape": "mcq",
      "tags": [
        "ebbinghaus",
        "forgetting-curve"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which researcher established the forgetting curve, and using what material?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Hermann Ebbinghaus, using nonsense syllables"
        },
        {
          "modality": "text",
          "value": "Henry Roediger, using nonsense syllables"
        },
        {
          "modality": "text",
          "value": "Hermann Ebbinghaus, using foreign-language vocabulary"
        },
        {
          "modality": "text",
          "value": "Henry Roediger, using foreign-language vocabulary"
        }
      ],
      "correctIndex": 0,
      "explanation": "Ebbinghaus ran self-experiments in the 1880s memorizing nonsense syllables — chosen precisely because they carried no prior meaning. Roediger and Karpicke are associated with the testing effect instead.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "enkxqarxihzq"
    },
    {
      "id": "ot-forget-4",
      "shape": "mcq",
      "tags": [
        "forgetting-curve",
        "decay"
      ],
      "prompt": {
        "modality": "text",
        "value": "According to Ebbinghaus, how does the rate of forgetting change across the first day after learning?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It starts slow for several hours, then accelerates sharply"
        },
        {
          "modality": "text",
          "value": "It rises steadily and peaks around the end of the first day"
        },
        {
          "modality": "text",
          "value": "It holds one constant pace from the first minute onward"
        },
        {
          "modality": "text",
          "value": "It is steepest right after learning and slows thereafter"
        }
      ],
      "correctIndex": 3,
      "explanation": "Ebbinghaus's curve is exponential, not linear: forgetting is fastest in the minutes and hours right after learning and slows from there. That early steepness is why a first review pays off most when it comes soon.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "d8ck7e14jo9di"
    },
    {
      "id": "ot-spacing-1",
      "shape": "mcq",
      "tags": [
        "spaced-repetition",
        "intervals"
      ],
      "prompt": {
        "modality": "text",
        "value": "Spaced repetition distributes study sessions over what kind of intervals?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Contracting intervals"
        },
        {
          "modality": "text",
          "value": "Expanding intervals"
        },
        {
          "modality": "text",
          "value": "Randomized intervals"
        },
        {
          "modality": "text",
          "value": "Uniform intervals"
        }
      ],
      "correctIndex": 1,
      "explanation": "Spaced repetition distributes sessions over expanding intervals, so each successful review buys a longer gap before the next. Fixed intervals ignore how the curve flattens with each review.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "xgn44g14km8go"
    },
    {
      "id": "ot-spacing-2",
      "shape": "mcq",
      "tags": [
        "spaced-repetition",
        "mechanism"
      ],
      "prompt": {
        "modality": "text",
        "value": "Why does reviewing material just before you would forget it beat the same total time spent cramming?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Spacing lets each trace consolidate before the next exposure, so passive re-reading lands on a settled memory",
          "short": "Traces consolidate before passive re-reading"
        },
        {
          "modality": "text",
          "value": "Retrieval at the memory's weakest point forces effortful encoding and resets the decay clock",
          "short": "Effortful retrieval resets the decay clock"
        },
        {
          "modality": "text",
          "value": "Retrieval at the memory's weakest point lets the old trace lapse and stores the answer as a brand-new memory",
          "short": "Old trace lapses; a fresh memory is stored"
        },
        {
          "modality": "text",
          "value": "Waiting until the memory is nearly gone shrinks the amount that has to be re-encoded, so each pass is cheaper",
          "short": "Near-forgetting shrinks what must be re-encoded"
        }
      ],
      "correctIndex": 1,
      "explanation": "You are forcing retrieval at the moment the memory is weakest, which triggers a more effortful encoding process and resets the decay clock. Cramming isn't harmful in itself — it simply wastes the timing advantage.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "d0zg9m1ytnrem"
    },
    {
      "id": "ot-spacing-3",
      "shape": "mcq",
      "tags": [
        "srs",
        "anki"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which pair of tools is named as SRS (Spaced Repetition Software)?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Duolingo and Quizlet"
        },
        {
          "modality": "text",
          "value": "Anki and SuperMemo"
        },
        {
          "modality": "text",
          "value": "Anki and Quizlet"
        },
        {
          "modality": "text",
          "value": "SuperMemo and Duolingo"
        }
      ],
      "correctIndex": 1,
      "explanation": "Anki and SuperMemo are the two SRS tools named in the guide — both algorithmically schedule each card at its optimal interval.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "kugbiqwbndly"
    },
    {
      "id": "ot-spacing-4",
      "shape": "mcq",
      "tags": [
        "srs",
        "scheduling"
      ],
      "prompt": {
        "modality": "text",
        "value": "On what basis does an SRS typically decide when to schedule a card's next review?"
      },
      "options": [
        {
          "modality": "text",
          "value": "How long you spent answering it last time"
        },
        {
          "modality": "text",
          "value": "How many other cards in the deck share its topic"
        },
        {
          "modality": "text",
          "value": "How confidently you recalled it last time"
        },
        {
          "modality": "text",
          "value": "How recently the card was added to the deck"
        }
      ],
      "correctIndex": 2,
      "explanation": "SRS scheduling is typically based on how confidently you recalled the card last time: easier cards get longer gaps, harder cards come back sooner. Card length and topic grouping don't drive the interval.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "hut8u978dvlv"
    },
    {
      "id": "ot-spacing-5",
      "shape": "mcq",
      "tags": [
        "srs",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "You recall a card easily and another only with great difficulty. How should an SRS schedule them?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Longer gap for the easy card, sooner review for the hard one"
        },
        {
          "modality": "text",
          "value": "Same gap for both cards, with the hard one shown first next session"
        },
        {
          "modality": "text",
          "value": "Sooner review for both cards, until each is recalled twice in a row"
        },
        {
          "modality": "text",
          "value": "Sooner review for the easy card, longer gap for the hard one"
        }
      ],
      "correctIndex": 0,
      "explanation": "Easier cards get longer gaps; harder cards are reviewed sooner. Identical gaps would waste time on material you already know while letting shaky material decay.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "ideqyms4l44i"
    },
    {
      "id": "ot-retrieval-1",
      "shape": "mcq",
      "tags": [
        "retrieval-practice",
        "definition"
      ],
      "prompt": {
        "modality": "text",
        "value": "Retrieval practice is defined as strengthening memory by doing what?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Highlighting key passages on each pass rather than reading every line",
          "short": "Highlighting over reading every line"
        },
        {
          "modality": "text",
          "value": "Actively recalling information rather than re-exposing yourself to it",
          "short": "Actively recalling information"
        },
        {
          "modality": "text",
          "value": "Re-reading until it feels familiar rather than stopping after one pass",
          "short": "Re-reading until familiar"
        },
        {
          "modality": "text",
          "value": "Spacing exposure across sessions rather than massing it into one block",
          "short": "Spacing exposure across sessions"
        }
      ],
      "correctIndex": 1,
      "explanation": "Retrieval practice means actively pulling information out of memory instead of re-exposing yourself to it — the mechanism behind the testing effect. Re-reading only confirms the information is accessible from the page.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "q7o29e1yctl2m"
    },
    {
      "id": "ot-retrieval-2",
      "shape": "mcq",
      "tags": [
        "karpicke-roediger",
        "evidence"
      ],
      "prompt": {
        "modality": "text",
        "value": "What did Karpicke & Roediger (2008) show about students who practiced retrieval versus those who restudied?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Restudiers retained significantly more after one week",
          "short": "Restudiers retained more"
        },
        {
          "modality": "text",
          "value": "Both groups retained roughly the same amount after one week",
          "short": "Both groups retained the same"
        },
        {
          "modality": "text",
          "value": "Retrieval practicers retained significantly more after one week",
          "short": "Retrieval group retained more"
        },
        {
          "modality": "text",
          "value": "Restudiers retained significantly more after one day",
          "short": "Restudiers retained more at one day"
        }
      ],
      "correctIndex": 2,
      "explanation": "Karpicke & Roediger (2008) found self-testing students retained significantly more after a week than those who restudied the same material the same number of times — equal exposure, unequal retention.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1tljq1zqugukt"
    },
    {
      "id": "ot-retrieval-3",
      "shape": "mcq",
      "tags": [
        "roediger-butler",
        "evidence"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which study confirmed retrieval practice's critical role in long-term retention across a range of material types?"
      },
      "options": [
        {
          "modality": "text",
          "value": "MIT Open Learning (2019)"
        },
        {
          "modality": "text",
          "value": "Roediger & Butler (2011)"
        },
        {
          "modality": "text",
          "value": "Ebbinghaus (1885)"
        },
        {
          "modality": "text",
          "value": "Karpicke & Roediger (2008)"
        }
      ],
      "correctIndex": 1,
      "explanation": "Roediger & Butler (2011) extended the finding beyond vocabulary to a range of material types. Karpicke & Roediger (2008) was the one-week restudy comparison; Ebbinghaus studied forgetting, not testing.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "9u9g2wny5ink"
    },
    {
      "id": "ot-retrieval-4",
      "shape": "mcq",
      "tags": [
        "production-effect",
        "difficulty"
      ],
      "prompt": {
        "modality": "text",
        "value": "Under the production effect, when does retrieval practice produce the largest gains?"
      },
      "options": [
        {
          "modality": "text",
          "value": "When retrieval is quick and successful"
        },
        {
          "modality": "text",
          "value": "When retrieval is quick and unsuccessful"
        },
        {
          "modality": "text",
          "value": "When retrieval is difficult but unsuccessful"
        },
        {
          "modality": "text",
          "value": "When retrieval is difficult but successful"
        }
      ],
      "correctIndex": 3,
      "explanation": "The effort of reconstructing an answer — difficult but successful retrieval — strengthens the memory trace most. Effortless retrieval yields smaller gains however often it is repeated, and a failed attempt lacks the successful reconstruction the effect depends on.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "136nnqv150i879"
    },
    {
      "id": "ot-behaviorism-founders-1",
      "shape": "mcq",
      "tags": [
        "skinner",
        "behaviorism",
        "pairs"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which behaviorism founder is correctly paired with his contribution?"
      },
      "options": [
        {
          "modality": "text",
          "value": "B.F. Skinner — operant conditioning"
        },
        {
          "modality": "text",
          "value": "Ivan Pavlov — conditioned reflexes in humans"
        },
        {
          "modality": "text",
          "value": "John Watson — classical conditioning with dogs"
        },
        {
          "modality": "text",
          "value": "Ivan Pavlov — reinforcement schedules"
        }
      ],
      "correctIndex": 0,
      "explanation": "The guide credits Skinner with operant conditioning — behavior shaped by its consequences — and with the insight that reinforcement schedules matter. Pavlov demonstrated classical conditioning with dogs; Watson extended conditioning to humans, treating all behavior as conditioned reflexes.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1882n371811jh5"
    },
    {
      "id": "ot-behaviorism-founders-2",
      "shape": "mcq",
      "tags": [
        "pavlov",
        "classical-conditioning"
      ],
      "prompt": {
        "modality": "text",
        "value": "Pavlov paired a bell with food until the bell alone triggered salivation in dogs. What did this demonstrate?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Operant conditioning"
        },
        {
          "modality": "text",
          "value": "Stimulus generalization"
        },
        {
          "modality": "text",
          "value": "Stimulus discrimination"
        },
        {
          "modality": "text",
          "value": "Classical conditioning"
        }
      ],
      "correctIndex": 3,
      "explanation": "This is classical conditioning: a neutral stimulus paired with a natural one until it alone triggers the response. Operant conditioning (Skinner) depends on the learner's own actions and their consequences; generalization and discrimination concern transfer to other stimuli.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "86a9801cd4smg"
    },
    {
      "id": "ot-behaviorism-founders-3",
      "shape": "mcq",
      "tags": [
        "watson",
        "behaviorism"
      ],
      "prompt": {
        "modality": "text",
        "value": "The guide names John Watson among the founders of which school of learning theory?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Connectivism"
        },
        {
          "modality": "text",
          "value": "Cognitivism"
        },
        {
          "modality": "text",
          "value": "Constructivism"
        },
        {
          "modality": "text",
          "value": "Behaviorism"
        }
      ],
      "correctIndex": 3,
      "explanation": "The guide lists Watson, with Skinner and Pavlov, among behaviorism's early-20th-century founders; he extended conditioning to humans, treating all behavior as conditioned reflexes.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "15y3w381jxedho"
    },
    {
      "id": "ot-behaviorism-founders-4",
      "shape": "mcq",
      "tags": [
        "behaviorism",
        "founders"
      ],
      "prompt": {
        "modality": "text",
        "value": "How did behaviorism's founders regard internal mental states such as beliefs and attention?"
      },
      "options": [
        {
          "modality": "text",
          "value": "As measurable and therefore fit for scientific study",
          "short": "Measurable, so worth studying"
        },
        {
          "modality": "text",
          "value": "As unmeasurable and therefore scientifically irrelevant",
          "short": "Unmeasurable, so irrelevant"
        },
        {
          "modality": "text",
          "value": "As unmeasurable yet still central to explaining learning",
          "short": "Unmeasurable but still central"
        },
        {
          "modality": "text",
          "value": "As measurable yet too unreliable to be worth studying",
          "short": "Measurable but too unreliable"
        }
      ],
      "correctIndex": 1,
      "explanation": "Skinner, Pavlov, and Watson argued that beliefs, feelings, and attention are unmeasurable and therefore scientifically irrelevant, so they treated the mind as a black box and studied only observable stimulus-response conditioning.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "sj912m1q7c1lm"
    },
    {
      "id": "ot-behaviorism-founders-5",
      "shape": "mcq",
      "tags": [
        "watson",
        "behaviorism",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "A trainer treats all human behavior as conditioned reflexes, extending a method first shown with dogs to people. Whose stance is this?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Ivan Pavlov's"
        },
        {
          "modality": "text",
          "value": "B.F. Skinner's"
        },
        {
          "modality": "text",
          "value": "John Watson's"
        },
        {
          "modality": "text",
          "value": "Albert Bandura's"
        }
      ],
      "correctIndex": 2,
      "explanation": "Watson extended conditioning to humans, treating all behavior as conditioned reflexes. Pavlov's demonstrations stayed with dogs, Skinner's operant conditioning turns on consequences rather than reflexes, and Bandura, a cognitivist, studied the internal processes behaviorism set aside.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "mos4m51dvmatz"
    },
    {
      "id": "ot-operant-shaping-1",
      "shape": "mcq",
      "tags": [
        "operant-conditioning",
        "skinner"
      ],
      "prompt": {
        "modality": "text",
        "value": "How does operant conditioning define what drives behavior change?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Behavior changes as mental schemas adjust — assimilation and accommodation",
          "short": "Adjusting existing schemas"
        },
        {
          "modality": "text",
          "value": "Behavior is shaped by its consequences — reinforcement and punishment",
          "short": "Shaped by its consequences"
        },
        {
          "modality": "text",
          "value": "Behavior is built between people, then within — culture and collaboration",
          "short": "Social first, then internalized"
        },
        {
          "modality": "text",
          "value": "Behavior is evoked by paired stimuli — a neutral cue and a natural one",
          "short": "Evoked by stimulus pairing"
        }
      ],
      "correctIndex": 1,
      "explanation": "Skinner's operant conditioning holds that consequences — reinforcement increases a behavior, punishment decreases it — shape it. Pairing two stimuli is Pavlov's classical conditioning; schema revision is Piaget's accommodation.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "187mt3o10qlpsk"
    },
    {
      "id": "ot-operant-shaping-2",
      "shape": "mcq",
      "tags": [
        "shaping",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "A coach rewards a beginner first for gripping the bat correctly, then for a partial swing, then for full contact. Which principle is this?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Fading"
        },
        {
          "modality": "text",
          "value": "Shaping"
        },
        {
          "modality": "text",
          "value": "Pairing"
        },
        {
          "modality": "text",
          "value": "Chunking"
        }
      ],
      "correctIndex": 1,
      "explanation": "Shaping rewards successive approximations toward a target behavior, teaching complex skills in small reinforced steps. Fading withdraws support as competence grows, pairing links a neutral stimulus to a natural one, and chunking groups items into larger units for encoding.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1vl8g7510n5di3"
    },
    {
      "id": "ot-operant-shaping-3",
      "shape": "mcq",
      "tags": [
        "reinforcement-schedules",
        "skinner"
      ],
      "prompt": {
        "modality": "text",
        "value": "What was Skinner's key insight about reinforcement schedules?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Punishment strengthens a behavior as much as reinforcement does",
          "short": "Punishment strengthens behavior"
        },
        {
          "modality": "text",
          "value": "Rewarding only a finished skill works as well as rewarding its steps",
          "short": "Whole-skill rewards work as well"
        },
        {
          "modality": "text",
          "value": "When a reward arrives matters as much as whether it arrives",
          "short": "Timing of rewards matters"
        },
        {
          "modality": "text",
          "value": "A behavior persists as well without its rewards as with them",
          "short": "Persists after rewards stop"
        }
      ],
      "correctIndex": 2,
      "explanation": "Skinner showed that timing matters: different reinforcement schedules produce different response rates and extinction curves, so one schedule does not sustain a behavior as well as another and when a reward arrives counts as much as whether it does.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "f3v94g4un1qg"
    },
    {
      "id": "ot-operant-shaping-4",
      "shape": "mcq",
      "tags": [
        "operant-conditioning",
        "compare"
      ],
      "prompt": {
        "modality": "text",
        "value": "What most clearly distinguishes Skinner's operant conditioning from Pavlov's conditioning?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Operant conditioning hinges on the learner's own actions",
          "short": "It hinges on the learner's actions"
        },
        {
          "modality": "text",
          "value": "Operant conditioning begins with the learner's reflex to a cue",
          "short": "It begins with a reflex to a cue"
        },
        {
          "modality": "text",
          "value": "Operant conditioning tracks the learner's beliefs and attention",
          "short": "It tracks beliefs and attention"
        },
        {
          "modality": "text",
          "value": "Operant conditioning relies on the learner's social interaction",
          "short": "It relies on social interaction"
        }
      ],
      "correctIndex": 0,
      "explanation": "Unlike Pavlov's passive stimulus pairing, in which a cue comes to trigger a reflex, operant conditioning is driven by the learner's own actions and their consequences.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1xq5fpf1g4v6gx"
    },
    {
      "id": "ot-piaget-processes-1",
      "shape": "mcq",
      "tags": [
        "assimilation",
        "piaget",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "A child who knows 'dog' sees a new breed and calls it a dog without changing what 'dog' means. Which process is this?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Accommodation"
        },
        {
          "modality": "text",
          "value": "Disequilibrium"
        },
        {
          "modality": "text",
          "value": "Assimilation"
        },
        {
          "modality": "text",
          "value": "Equilibration"
        }
      ],
      "correctIndex": 2,
      "explanation": "Assimilation integrates new information into an existing schema without altering it. Accommodation would be required only if the new case contradicted the schema and forced it to be revised.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1bfmboq19zg2na"
    },
    {
      "id": "ot-piaget-processes-2",
      "shape": "mcq",
      "tags": [
        "accommodation",
        "piaget"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which Piagetian process involves modifying an existing schema to incorporate contradictory new information?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Equilibration"
        },
        {
          "modality": "text",
          "value": "Assimilation"
        },
        {
          "modality": "text",
          "value": "Disequilibrium"
        },
        {
          "modality": "text",
          "value": "Accommodation"
        }
      ],
      "correctIndex": 3,
      "explanation": "Accommodation revises the schema itself when new information contradicts it — a more effortful process that produces genuine conceptual change. Assimilation leaves the schema intact; disequilibrium is the tension the contradiction creates, and equilibration the drive to resolve it.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "9zyzw5mevk2v"
    },
    {
      "id": "ot-piaget-processes-3",
      "shape": "mcq",
      "tags": [
        "equilibration",
        "piaget"
      ],
      "prompt": {
        "modality": "text",
        "value": "In Piaget's account, what is equilibration?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The drive to balance assimilation and accommodation and resolve schema tension",
          "short": "Drive to rebalance and resolve"
        },
        {
          "modality": "text",
          "value": "The stored pattern that assimilation preserves and accommodation revises",
          "short": "Stored pattern that gets revised"
        },
        {
          "modality": "text",
          "value": "The tension between a stored schema and new experience that contradicts it",
          "short": "Tension from a schema conflict"
        },
        {
          "modality": "text",
          "value": "The effortful revision of a schema so that surprising new experience fits it",
          "short": "Effortful revision of a schema"
        }
      ],
      "correctIndex": 0,
      "explanation": "Equilibration is the drive to resolve the tension between old schemas and new information by balancing assimilation and accommodation. The tension itself is disequilibrium, the stored pattern is the schema, and the effortful revision is accommodation.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1uh9e2s1fdtjas"
    },
    {
      "id": "ot-piaget-processes-4",
      "shape": "mcq",
      "tags": [
        "equilibration",
        "piaget",
        "sequence"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which sequence correctly orders Piaget's engine of cognitive development?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Accommodation revises a schema → disequilibrium → assimilation restores the original pattern",
          "short": "Accommodate → disequilibrium → assimilate"
        },
        {
          "modality": "text",
          "value": "Equilibration produces a schema → new information contradicts it → disequilibrium drives assimilation",
          "short": "Equilibrate → contradiction → assimilate"
        },
        {
          "modality": "text",
          "value": "New information conflicts with a schema → disequilibrium → equilibration drives accommodation",
          "short": "Conflict → disequilibrium → accommodate"
        },
        {
          "modality": "text",
          "value": "New information fits a schema → assimilation → equilibration then drives accommodation",
          "short": "Fit → assimilate → accommodate"
        }
      ],
      "correctIndex": 2,
      "explanation": "Conflict between an existing schema and new experience creates disequilibrium; equilibration is the drive to resolve it, often via accommodation. Information that fits is simply assimilated with the schema intact, and accommodation is the resolution of conflict rather than its trigger.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1io0l6w4le6ig"
    },
    {
      "id": "ot-schema-chunking-1",
      "shape": "mcq",
      "tags": [
        "schema",
        "definition"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which best describes what a schema is?"
      },
      "options": [
        {
          "modality": "text",
          "value": "A grouping of raw items into meaningful units that occupy fewer memory slots",
          "short": "Grouping items into meaningful units"
        },
        {
          "modality": "text",
          "value": "A cognitive framework or category used to organize and interpret information",
          "short": "Framework to organize information"
        },
        {
          "modality": "text",
          "value": "A reinforcement schedule or timing pattern that governs response rate and extinction",
          "short": "Pattern governing response rate"
        },
        {
          "modality": "text",
          "value": "A temporary support or prompt that is withdrawn as the learner's competence grows",
          "short": "Support removed as skill grows"
        }
      ],
      "correctIndex": 1,
      "explanation": "A schema is a cognitive framework — a stored pattern of understanding — used to organize and interpret information. Grouping items into meaningful units is chunking; temporary support is scaffolding.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "10lv0wesjwutu"
    },
    {
      "id": "ot-schema-chunking-2",
      "shape": "mcq",
      "tags": [
        "miller",
        "working-memory"
      ],
      "prompt": {
        "modality": "text",
        "value": "George Miller's landmark 1956 paper established what capacity for working memory?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Roughly 9 ± 3 chunks"
        },
        {
          "modality": "text",
          "value": "Roughly 7 ± 2 chunks"
        },
        {
          "modality": "text",
          "value": "Roughly 5 ± 2 chunks"
        },
        {
          "modality": "text",
          "value": "Roughly 3 ± 1 chunks"
        }
      ],
      "correctIndex": 1,
      "explanation": "Miller's 1956 paper established that working memory holds roughly 7 ± 2 chunks at once — a hard capacity limit that has shaped instructional design ever since.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1xs7y1d1qohhkr"
    },
    {
      "id": "ot-schema-chunking-3",
      "shape": "mcq",
      "tags": [
        "chunking",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "Why does turning the digits 1-4-9-2 into '1492' help memory?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It reduces the number of working-memory slots occupied by grouping items into one meaningful unit",
          "short": "Groups items into one WM slot"
        },
        {
          "modality": "text",
          "value": "It raises working memory's capacity by training it to hold more chunks at once",
          "short": "Trains WM to hold more chunks"
        },
        {
          "modality": "text",
          "value": "It sends the digits straight to long-term storage by skipping working memory altogether",
          "short": "Skips WM, goes to long-term"
        },
        {
          "modality": "text",
          "value": "It lowers the cognitive load of each digit by spreading the four across separate slots",
          "short": "Spreads digits across WM slots"
        }
      ],
      "correctIndex": 0,
      "explanation": "Chunking groups raw items into meaningful units, so fewer of working memory's ~7±2 slots are occupied and encoding improves. Chunking works within the capacity limit rather than raising it.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "czqnsii7euhq"
    },
    {
      "id": "ot-schema-chunking-4",
      "shape": "mcq",
      "tags": [
        "schema",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "A diner handles an unfamiliar restaurant using a stored pattern — be seated, read the menu, order, pay. What is that stored pattern called?"
      },
      "options": [
        {
          "modality": "text",
          "value": "A scaffold"
        },
        {
          "modality": "text",
          "value": "A stimulus"
        },
        {
          "modality": "text",
          "value": "A chunk"
        },
        {
          "modality": "text",
          "value": "A schema"
        }
      ],
      "correctIndex": 3,
      "explanation": "A schema is the cognitive framework used to organize and interpret new information. A chunk groups raw items into one memory unit, a scaffold is temporary instructional support, and a stimulus is the input that triggers a response, not the stored pattern that interprets it.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "2prwgrpx3bdt"
    },
    {
      "id": "ot-schema-chunking-5",
      "shape": "mcq",
      "tags": [
        "chunking",
        "cognitive-load"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which is NOT an accurate description of chunking?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It permanently raises the number of chunks working memory can hold",
          "short": "Permanently raises WM's limit"
        },
        {
          "modality": "text",
          "value": "It always groups multiple raw items into larger meaningful units",
          "short": "Always groups items into larger units"
        },
        {
          "modality": "text",
          "value": "It lets each occupied slot carry far more meaning than a raw item",
          "short": "Each slot carries far more meaning"
        },
        {
          "modality": "text",
          "value": "It sharply reduces the number of slots occupied and improves encoding",
          "short": "Sharply cuts slots, aids encoding"
        }
      ],
      "correctIndex": 0,
      "explanation": "Chunking exploits the ~7±2 limit by packing more meaning into each slot; it does not raise the limit itself. The other three statements match the lesson's definition of chunking.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "w7m9h51u4jpo3"
    },
    {
      "id": "ot-constructivism-1",
      "shape": "mcq",
      "tags": [
        "zpd",
        "vygotsky",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "According to Vygotsky, learning is most efficient when a task sits where?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Inside the gap between independent ability and guided ability",
          "short": "Between solo and guided ability"
        },
        {
          "modality": "text",
          "value": "Inside the range the learner already handles confidently on their own",
          "short": "Within what they handle alone"
        },
        {
          "modality": "text",
          "value": "Just beyond what a more knowledgeable other could guide the learner through",
          "short": "Just beyond what an MKO can guide"
        },
        {
          "modality": "text",
          "value": "Inside the gap between a peer's ability and a trained teacher's ability",
          "short": "Between a peer's and a teacher's"
        }
      ],
      "correctIndex": 0,
      "explanation": "A task inside the ZPD is hard enough to need support but not so hard it frustrates: too easy and no growth occurs, too hard and progress blocks. The zone is measured against the learner's own independent and guided ability, not against what a peer or teacher can do.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "icido8mz7myo"
    },
    {
      "id": "ot-constructivism-2",
      "shape": "mcq",
      "tags": [
        "scaffolding",
        "fading"
      ],
      "prompt": {
        "modality": "text",
        "value": "What design constraint separates effective scaffolding from simply making a task easier?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Scaffolds must be temporary and progressively withdrawn through fading",
          "short": "Temporary, faded out over time"
        },
        {
          "modality": "text",
          "value": "Scaffolds must be pitched at the level the learner already reaches alone",
          "short": "Pitched at the current solo level"
        },
        {
          "modality": "text",
          "value": "Scaffolds must be increased step by step as the learner's accuracy improves",
          "short": "Increased as accuracy improves"
        },
        {
          "modality": "text",
          "value": "Scaffolds must be supplied by a trained teacher acting as the more knowledgeable other",
          "short": "Trained teacher acting as the MKO"
        }
      ],
      "correctIndex": 0,
      "explanation": "Scaffolding is temporary by design: support fades as competence grows. Scaffolds never removed create dependency, a 'more knowledgeable other' can be a peer or structured tool, not only a teacher, and pitching the task at what the learner already does alone produces no growth.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "xf0nj91i0onqv"
    },
    {
      "id": "ot-constructivism-3",
      "shape": "mcq",
      "tags": [
        "dewey",
        "pairs"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which theorist is matched with 'learn by doing' — authentic problems, real consequences, and reflection on action?"
      },
      "options": [
        {
          "modality": "text",
          "value": "John Dewey"
        },
        {
          "modality": "text",
          "value": "Jean Piaget"
        },
        {
          "modality": "text",
          "value": "Albert Bandura"
        },
        {
          "modality": "text",
          "value": "Lev Vygotsky"
        }
      ],
      "correctIndex": 0,
      "explanation": "Dewey's pragmatic constructivism insisted on 'learn by doing'. Vygotsky is matched with the ZPD and social constructivism, Piaget with cognitive constructivism, and Bandura with the cognitivist study of the mind's internal processes.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1tkffxy1nl31oi"
    },
    {
      "id": "ot-constructivism-4",
      "shape": "mcq",
      "tags": [
        "vygotsky",
        "constructivism",
        "compare"
      ],
      "prompt": {
        "modality": "text",
        "value": "How does Vygotsky's social constructivism differ from Piaget's cognitive constructivism?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It holds that higher mental functions mature within the individual before they are shared socially",
          "short": "Functions mature inside, then shared"
        },
        {
          "modality": "text",
          "value": "It treats reflection on authentic problems with real consequences as the engine of learning",
          "short": "Real problems and reflection drive it"
        },
        {
          "modality": "text",
          "value": "It holds that higher mental functions arise between people before becoming internal",
          "short": "Higher functions form between people"
        },
        {
          "modality": "text",
          "value": "It emphasizes the individual mind's encounter with the physical world through exploration",
          "short": "Individual mind meets physical world"
        }
      ],
      "correctIndex": 2,
      "explanation": "Vygotsky argued higher mental functions arise first between people, then become internal — learning is inherently social. The individual's encounter with the physical world is Piaget's emphasis, and learning by doing through authentic problems is Dewey's.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "6bcey4faasxw"
    },
    {
      "id": "ot-blooms-structure-1",
      "shape": "mcq",
      "tags": [
        "blooms-taxonomy",
        "history"
      ],
      "prompt": {
        "modality": "text",
        "value": "Who published the original Taxonomy of Educational Objectives: Cognitive Domain, and in what year?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Benjamin Bloom and colleagues, 1956"
        },
        {
          "modality": "text",
          "value": "Lorin Anderson and David Krathwohl, 1956"
        },
        {
          "modality": "text",
          "value": "Lorin Anderson and David Krathwohl, 2001"
        },
        {
          "modality": "text",
          "value": "Benjamin Bloom and colleagues, 2001"
        }
      ],
      "correctIndex": 0,
      "explanation": "Bloom and colleagues at the University of Chicago published the original cognitive taxonomy in 1956. Anderson and Krathwohl published the 2001 revision, not the original, and 2001 is the revision's date rather than the taxonomy's.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "p4q7f6fcfupa"
    },
    {
      "id": "ot-blooms-structure-2",
      "shape": "mcq",
      "tags": [
        "blooms-taxonomy",
        "2001-revision"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which mapping from a 1956 level to its 2001 counterpart is correct?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Knowledge to Understand"
        },
        {
          "modality": "text",
          "value": "Synthesis to Create"
        },
        {
          "modality": "text",
          "value": "Analysis to Evaluate"
        },
        {
          "modality": "text",
          "value": "Comprehension to Apply"
        }
      ],
      "correctIndex": 1,
      "explanation": "Synthesis was renamed Create and moved to the summit. Each wrong pairing slips one rung too high: Knowledge became Remember, Comprehension became Understand, and Analysis became Analyze.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "2hni9m170erfq"
    },
    {
      "id": "ot-blooms-structure-3",
      "shape": "mcq",
      "tags": [
        "2001-revision",
        "structure"
      ],
      "prompt": {
        "modality": "text",
        "value": "What did the 2001 revision do to the number of levels in the cognitive taxonomy?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It kept the taxonomy at its original five levels"
        },
        {
          "modality": "text",
          "value": "It expanded the taxonomy from five levels to six"
        },
        {
          "modality": "text",
          "value": "It cut the taxonomy from six levels to five"
        },
        {
          "modality": "text",
          "value": "It kept the taxonomy at its original six levels"
        }
      ],
      "correctIndex": 3,
      "explanation": "The revision renamed the levels and reordered the top two but kept all six. Five is the level count of the affective domain, not the cognitive taxonomy, and nothing was added or cut.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1emxyuh1vhujq3"
    },
    {
      "id": "ot-blooms-structure-4",
      "shape": "mcq",
      "tags": [
        "blooms-taxonomy",
        "1956"
      ],
      "prompt": {
        "modality": "text",
        "value": "In the original 1956 taxonomy, which level sat at the very top of the hierarchy?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Evaluation"
        },
        {
          "modality": "text",
          "value": "Synthesis"
        },
        {
          "modality": "text",
          "value": "Analysis"
        },
        {
          "modality": "text",
          "value": "Application"
        }
      ],
      "correctIndex": 0,
      "explanation": "In 1956 the order ended Synthesis then Evaluation, so Evaluation was the summit. The 2001 revision swapped them, dropping Evaluate one rung below Create.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1mrg3y1qbsvmy"
    },
    {
      "id": "ot-blooms-structure-5",
      "shape": "mcq",
      "tags": [
        "2001-revision",
        "objectives"
      ],
      "prompt": {
        "modality": "text",
        "value": "An instructor rewrites 'the student will demonstrate Analysis' as 'the student will break down the argument.' Which 2001 change does this reflect?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The hierarchy was flattened, making every level equally rigorous",
          "short": "Hierarchy flattened, all equal"
        },
        {
          "modality": "text",
          "value": "The affective domain was folded in, making attitudes a cognitive level",
          "short": "Affective domain folded in"
        },
        {
          "modality": "text",
          "value": "Level names became verbs, making objectives directly actionable",
          "short": "Level names became action verbs"
        },
        {
          "modality": "text",
          "value": "The top two levels were swapped, making judgment the final rung",
          "short": "Top two swapped, judgment on top"
        }
      ],
      "correctIndex": 2,
      "explanation": "The verb shift forces a clearer choice of evidence than the noun form. The top-two swap put Create, not Evaluate, at the summit; the levels still rank, and the affective domain stayed a separate 1964 handbook.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "jed7fwcrzqpo"
    },
    {
      "id": "ot-affective-1",
      "shape": "mcq",
      "tags": [
        "affective-domain",
        "levels"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which is the lowest level of Bloom's affective domain — simply attending to a stimulus?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Organizing"
        },
        {
          "modality": "text",
          "value": "Responding"
        },
        {
          "modality": "text",
          "value": "Valuing"
        },
        {
          "modality": "text",
          "value": "Receiving"
        }
      ],
      "correctIndex": 3,
      "explanation": "Receiving is the entry level: merely attending to a stimulus. Responding is the next rung, where the learner actively reacts rather than just notices.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "369y77107uiu9"
    },
    {
      "id": "ot-affective-2",
      "shape": "mcq",
      "tags": [
        "affective-domain",
        "levels"
      ],
      "prompt": {
        "modality": "text",
        "value": "In the affective domain, which level describes a value system that has become integrated into a person's identity?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Characterizing"
        },
        {
          "modality": "text",
          "value": "Organizing"
        },
        {
          "modality": "text",
          "value": "Responding"
        },
        {
          "modality": "text",
          "value": "Valuing"
        }
      ],
      "correctIndex": 0,
      "explanation": "Characterizing is the top level, where a value system is integrated into identity. Valuing and Organizing are lower rungs on the same ladder, short of that full internalization.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1makyidun7nq7"
    },
    {
      "id": "ot-affective-3",
      "shape": "mcq",
      "tags": [
        "affective-domain",
        "levels"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which of these is one of the five levels of Bloom's affective domain?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Believing"
        },
        {
          "modality": "text",
          "value": "Feeling"
        },
        {
          "modality": "text",
          "value": "Valuing"
        },
        {
          "modality": "text",
          "value": "Trusting"
        }
      ],
      "correctIndex": 2,
      "explanation": "The affective five are Receiving, Responding, Valuing, Organizing, Characterizing. Reflecting, Believing and Committing sound affective but name no level in the 1964 handbook.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1evhe9g1w1rg0k"
    },
    {
      "id": "ot-affective-4",
      "shape": "mcq",
      "tags": [
        "affective-domain",
        "history"
      ],
      "prompt": {
        "modality": "text",
        "value": "In what year did Bloom's team publish the second handbook covering the affective domain?"
      },
      "options": [
        {
          "modality": "text",
          "value": "1984"
        },
        {
          "modality": "text",
          "value": "2001"
        },
        {
          "modality": "text",
          "value": "1956"
        },
        {
          "modality": "text",
          "value": "1964"
        }
      ],
      "correctIndex": 3,
      "explanation": "The affective handbook came in 1964. 1956 was the original cognitive taxonomy, 1984 the 2 Sigma paper, and 2001 the Anderson and Krathwohl revision.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "16ktx2jpdp4r5"
    },
    {
      "id": "ot-verb-ladder-1",
      "shape": "mcq",
      "tags": [
        "verb-ladder",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which set of action verbs belongs to the Apply level?"
      },
      "options": [
        {
          "modality": "text",
          "value": "design, produce, construct, invent"
        },
        {
          "modality": "text",
          "value": "define, list, recall, identify"
        },
        {
          "modality": "text",
          "value": "recognize, describe, summarize, explain"
        },
        {
          "modality": "text",
          "value": "use, execute, implement, solve"
        }
      ],
      "correctIndex": 3,
      "explanation": "Apply is about putting knowledge to use: use, execute, implement, solve. 'define, list, recall, identify' are Remember verbs — lower-order retrieval, not use.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "scvubb5ecuth"
    },
    {
      "id": "ot-verb-ladder-2",
      "shape": "mcq",
      "tags": [
        "verb-ladder",
        "create"
      ],
      "prompt": {
        "modality": "text",
        "value": "An objective reads 'the student will design and produce an original experiment.' Which revised level do those verbs place it at?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Analyze"
        },
        {
          "modality": "text",
          "value": "Apply"
        },
        {
          "modality": "text",
          "value": "Create"
        },
        {
          "modality": "text",
          "value": "Evaluate"
        }
      ],
      "correctIndex": 2,
      "explanation": "Design and produce are Create verbs — original production, the summit of the revised ladder. Apply verbs (use, execute, implement, solve) work an existing method rather than making something new.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "f5bhxm1s4b3zy"
    },
    {
      "id": "ot-verb-ladder-3",
      "shape": "mcq",
      "tags": [
        "verb-ladder",
        "remember"
      ],
      "prompt": {
        "modality": "text",
        "value": "The verbs 'define, list, recall, identify' correspond to which revised Bloom level?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Apply"
        },
        {
          "modality": "text",
          "value": "Analyze"
        },
        {
          "modality": "text",
          "value": "Remember"
        },
        {
          "modality": "text",
          "value": "Understand"
        }
      ],
      "correctIndex": 2,
      "explanation": "These are retrieval verbs, so they sit at Remember, the lowest rung. Understand would require explaining or summarizing rather than simply recalling.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1167qvi1qdhflm"
    },
    {
      "id": "ot-verb-ladder-4",
      "shape": "mcq",
      "tags": [
        "verb-ladder",
        "hierarchy"
      ],
      "prompt": {
        "modality": "text",
        "value": "In the revised taxonomy, which level sits directly below the summit?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Analyze"
        },
        {
          "modality": "text",
          "value": "Create"
        },
        {
          "modality": "text",
          "value": "Remember"
        },
        {
          "modality": "text",
          "value": "Evaluate"
        }
      ],
      "correctIndex": 3,
      "explanation": "The revision put Create at the summit with Evaluate one rung below. Create is the summit itself, not the level beneath it, and Analyze sits two rungs down, above Apply.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1b9w1ad3nfpu7"
    },
    {
      "id": "ot-two-sigma-1",
      "shape": "mcq",
      "tags": [
        "two-sigma",
        "effect-size"
      ],
      "prompt": {
        "modality": "text",
        "value": "In Bloom's 1984 study, the average tutored student outperformed roughly what share of the conventionally taught control class?"
      },
      "options": [
        {
          "modality": "text",
          "value": "68%"
        },
        {
          "modality": "text",
          "value": "84%"
        },
        {
          "modality": "text",
          "value": "50%"
        },
        {
          "modality": "text",
          "value": "98%"
        }
      ],
      "correctIndex": 3,
      "explanation": "A two standard deviation gain puts the average tutored student above about 98% of the control class. 84% would correspond to a one-sigma gain, the level mastery learning alone reached.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1n4v062gl7qu"
    },
    {
      "id": "ot-two-sigma-2",
      "shape": "mcq",
      "tags": [
        "two-sigma",
        "study-design"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which three instructional conditions did Bloom compare in his 1984 study?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Conventional teaching, programmed instruction, and computer-assisted drill",
          "short": "Conventional + programmed + computer drill"
        },
        {
          "modality": "text",
          "value": "Lecture-based teaching, small-group seminars, and peer tutoring in pairs",
          "short": "Lecture + seminars + peer tutoring"
        },
        {
          "modality": "text",
          "value": "Conventional teaching, classroom mastery learning, and one-to-one tutoring",
          "short": "Conventional + mastery + one-to-one tutoring"
        },
        {
          "modality": "text",
          "value": "Classroom mastery learning, cooperative learning, and peer tutoring in pairs",
          "short": "Mastery + cooperative + peer tutoring"
        }
      ],
      "correctIndex": 2,
      "explanation": "Bloom's 1984 comparison had three arms: conventional classroom teaching, mastery learning in a classroom, and one-to-one tutoring with mastery techniques.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1m786662rrvs2"
    },
    {
      "id": "ot-two-sigma-3",
      "shape": "mcq",
      "tags": [
        "mastery-learning",
        "history"
      ],
      "prompt": {
        "modality": "text",
        "value": "Mastery learning was developed earlier by whom, before Bloom expanded it?"
      },
      "options": [
        {
          "modality": "text",
          "value": "John Carroll"
        },
        {
          "modality": "text",
          "value": "Robert Gagne"
        },
        {
          "modality": "text",
          "value": "David Krathwohl"
        },
        {
          "modality": "text",
          "value": "Lorin Anderson"
        }
      ],
      "correctIndex": 0,
      "explanation": "John Carroll developed mastery learning and Bloom expanded it. Anderson and Krathwohl are associated with the 2001 taxonomy revision, not mastery learning.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1b8lwsu1nkgms2"
    },
    {
      "id": "ot-alterable-1",
      "shape": "mcq",
      "tags": [
        "alterable-variables",
        "ranking"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which alterable variable topped Bloom's list with the largest effect size?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Reinforcement in the classroom"
        },
        {
          "modality": "text",
          "value": "Cooperative learning in small groups"
        },
        {
          "modality": "text",
          "value": "One-to-one tutorial instruction"
        },
        {
          "modality": "text",
          "value": "Feedback-corrective mastery learning"
        }
      ],
      "correctIndex": 2,
      "explanation": "One-to-one tutorial instruction led at 2 sigma. Reinforcement was second at 1.2 sigma — large, but only about half the tutoring effect.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "12ua7cuib9cay"
    },
    {
      "id": "ot-alterable-2",
      "shape": "mcq",
      "tags": [
        "alterable-variables",
        "effect-size"
      ],
      "prompt": {
        "modality": "text",
        "value": "What effect size did Bloom report for reinforcement?"
      },
      "options": [
        {
          "modality": "text",
          "value": "2.0 sigma"
        },
        {
          "modality": "text",
          "value": "1.2 sigma"
        },
        {
          "modality": "text",
          "value": "0.8 sigma"
        },
        {
          "modality": "text",
          "value": "1.0 sigma"
        }
      ],
      "correctIndex": 1,
      "explanation": "Reinforcement came second at 1.2 sigma. The 2 sigma figure belongs to one-to-one tutorial instruction, which topped the list.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "d635ev6mc93h"
    },
    {
      "id": "ot-alterable-3",
      "shape": "mcq",
      "tags": [
        "alterable-variables",
        "effect-size"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which two alterable variables each reached 1 sigma?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Cooperative learning, and one-to-one tutorial instruction",
          "short": "Cooperative learning + one-to-one tutoring"
        },
        {
          "modality": "text",
          "value": "Mastery learning with feedback-corrective cycles, and student time on task",
          "short": "Mastery learning + time on task"
        },
        {
          "modality": "text",
          "value": "Reinforcement, and mastery learning with feedback-corrective cycles",
          "short": "Reinforcement + mastery learning"
        },
        {
          "modality": "text",
          "value": "One-to-one tutorial instruction, and student time on task",
          "short": "One-to-one tutoring + time on task"
        }
      ],
      "correctIndex": 1,
      "explanation": "Feedback-corrective mastery learning and time on task each hit 1 sigma. One-to-one tutorial instruction sits at 2 sigma, reinforcement at 1.2 and cooperative learning at 0.8, so every pair containing one of those misses the mark.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1k9a3p210jux82"
    },
    {
      "id": "ot-alterable-4",
      "shape": "mcq",
      "tags": [
        "alterable-variables",
        "effect-size"
      ],
      "prompt": {
        "modality": "text",
        "value": "What effect size did Bloom assign to classroom morale?"
      },
      "options": [
        {
          "modality": "text",
          "value": "0.8 sigma"
        },
        {
          "modality": "text",
          "value": "1 sigma"
        },
        {
          "modality": "text",
          "value": "0.6 sigma"
        },
        {
          "modality": "text",
          "value": "1.2 sigma"
        }
      ],
      "correctIndex": 2,
      "explanation": "Classroom morale sat at the bottom of the ranking at 0.6 sigma. 0.8 sigma belongs to cooperative learning and graded homework, the next rung up.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1p8bpwj13nrjuh"
    },
    {
      "id": "ot-alterable-5",
      "shape": "mcq",
      "tags": [
        "alterable-variables",
        "ranking"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which list ranks alterable variables correctly from largest effect size to smallest?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Classroom morale, graded homework, time on task"
        },
        {
          "modality": "text",
          "value": "Mastery learning, reinforcement, cooperative learning"
        },
        {
          "modality": "text",
          "value": "Time on task, reinforcement, graded homework"
        },
        {
          "modality": "text",
          "value": "Reinforcement, cooperative learning, classroom morale"
        }
      ],
      "correctIndex": 3,
      "explanation": "Reinforcement 1.2, cooperative learning 0.8, classroom morale 0.6 — a correct descending order. Every other option puts a smaller effect ahead of a larger one.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "5ygetliybpdv"
    },
    {
      "id": "ot-flow-autotelic-1",
      "shape": "mcq",
      "tags": [
        "flow",
        "autotelic",
        "motivation"
      ],
      "prompt": {
        "modality": "text",
        "value": "A student keeps practicing piano long after the assignment is finished, purely because playing itself is rewarding. Flow theory calls this kind of activity:"
      },
      "options": [
        {
          "modality": "text",
          "value": "Exotelic"
        },
        {
          "modality": "text",
          "value": "Vicarious"
        },
        {
          "modality": "text",
          "value": "Habitual"
        },
        {
          "modality": "text",
          "value": "Autotelic"
        }
      ],
      "correctIndex": 3,
      "explanation": "Autotelic means rewarding in itself, with no external payoff — the mark of flow. Exotelic and extrinsic both describe activity pursued for an outside reward, the opposite case; vicarious describes learning by watching someone else act.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "17vy73s1gb5ds"
    },
    {
      "id": "ot-flow-mastery-2",
      "shape": "mcq",
      "tags": [
        "flow",
        "research",
        "mastery"
      ],
      "prompt": {
        "modality": "text",
        "value": "Research found that flow-optimized learning environments accelerated mastery by roughly what factor?"
      },
      "options": [
        {
          "modality": "text",
          "value": "3.7×"
        },
        {
          "modality": "text",
          "value": "2.3×"
        },
        {
          "modality": "text",
          "value": "1.4×"
        },
        {
          "modality": "text",
          "value": "5.0×"
        }
      ],
      "correctIndex": 1,
      "explanation": "The reported figure is about 2.3× faster mastery in flow-optimized environments — a substantial but not extraordinary gain, which is why the larger factors are wrong.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "13vgujo1gtblk4"
    },
    {
      "id": "ot-flow-burnout-3",
      "shape": "mcq",
      "tags": [
        "flow",
        "burnout",
        "research"
      ],
      "prompt": {
        "modality": "text",
        "value": "Flow-optimized learning environments were found to reduce learner burnout by roughly how much?"
      },
      "options": [
        {
          "modality": "text",
          "value": "68%"
        },
        {
          "modality": "text",
          "value": "12%"
        },
        {
          "modality": "text",
          "value": "27%"
        },
        {
          "modality": "text",
          "value": "41%"
        }
      ],
      "correctIndex": 3,
      "explanation": "The reported reduction in learner burnout is about 41%. Keeping challenge matched to skill avoids the anxiety of overload, which is what drives burnout down.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "giazjsthha0"
    },
    {
      "id": "ot-dual-paivio-1",
      "shape": "mcq",
      "tags": [
        "dual coding",
        "Paivio",
        "attribution"
      ],
      "prompt": {
        "modality": "text",
        "value": "Who proposed Dual Coding Theory, and in what year?"
      },
      "options": [
        {
          "modality": "text",
          "value": "John Sweller, 1988"
        },
        {
          "modality": "text",
          "value": "George Siemens, 2004"
        },
        {
          "modality": "text",
          "value": "Robert Gagné, 1965"
        },
        {
          "modality": "text",
          "value": "Allan Paivio, 1971"
        }
      ],
      "correctIndex": 3,
      "explanation": "Allan Paivio proposed Dual Coding Theory in 1971. Sweller (1988) gave us Cognitive Load Theory and Gagné (1965) the Conditions of Learning — different theories entirely.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1u81yl21l8cgc2"
    },
    {
      "id": "ot-dual-systems-2",
      "shape": "mcq",
      "tags": [
        "dual coding",
        "memory systems"
      ],
      "prompt": {
        "modality": "text",
        "value": "Dual Coding Theory holds that humans operate with which two interconnected memory systems?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Episodic and semantic"
        },
        {
          "modality": "text",
          "value": "Verbal and visual"
        },
        {
          "modality": "text",
          "value": "Working and long-term"
        },
        {
          "modality": "text",
          "value": "Implicit and explicit"
        }
      ],
      "correctIndex": 1,
      "explanation": "Paivio's model pairs a verbal system (language, text, narrative) with a visual system (imagery, spatial layout). Episodic/semantic, working/long-term and implicit/explicit are all real memory distinctions, but none is the pair Dual Coding Theory is built on.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "wh1ys913ww33n"
    },
    {
      "id": "ot-dual-not-3",
      "shape": "mcq",
      "tags": [
        "dual coding",
        "theory"
      ],
      "prompt": {
        "modality": "text",
        "value": "In Paivio's Dual Coding Theory, how do the verbal and visual memory systems relate to each other?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Interconnected, with both required to encode any information"
        },
        {
          "modality": "text",
          "value": "Interconnected, with just the verbal system able to encode alone"
        },
        {
          "modality": "text",
          "value": "Interconnected, with just the visual system able to encode alone"
        },
        {
          "modality": "text",
          "value": "Interconnected, with each able to encode information on its own"
        }
      ],
      "correctIndex": 3,
      "explanation": "Paivio describes the verbal and visual systems as interconnected: each can encode information independently, and learning improves when both are engaged at once. They remain two systems rather than one merged trace, and neither recodes for or directs the other.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "m7ow5q1b3onnu"
    },
    {
      "id": "ot-dual-apply-4",
      "shape": "mcq",
      "tags": [
        "dual coding",
        "application"
      ],
      "prompt": {
        "modality": "text",
        "value": "A lesson pairs a labeled diagram with a spoken explanation. Under Dual Coding Theory, why does this pairing help learning?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It splits the material so each channel encodes only half"
        },
        {
          "modality": "text",
          "value": "It merges the two channels into one stronger trace"
        },
        {
          "modality": "text",
          "value": "It encodes the material in the two channels one after the other"
        },
        {
          "modality": "text",
          "value": "It encodes the material through both memory channels at once"
        }
      ],
      "correctIndex": 3,
      "explanation": "The diagram engages the visual system while the spoken explanation engages the verbal one, so the same material is encoded twice, at the same time. The channels stay distinct: the material is neither split between them, merged into one trace, nor passed through them one after the other.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "14ppeul14489q7"
    },
    {
      "id": "ot-dual-onechannel-5",
      "shape": "mcq",
      "tags": [
        "dual coding",
        "compare"
      ],
      "prompt": {
        "modality": "text",
        "value": "Per Dual Coding Theory, which of these encodes information in only ONE channel?"
      },
      "options": [
        {
          "modality": "text",
          "value": "A labeled anatomy diagram"
        },
        {
          "modality": "text",
          "value": "A wall of unbroken text"
        },
        {
          "modality": "text",
          "value": "A captioned photograph"
        },
        {
          "modality": "text",
          "value": "A mnemonic image for a word"
        }
      ],
      "correctIndex": 1,
      "explanation": "Text alone engages just the verbal system. The other three each combine imagery with language, engaging both channels — the whole point of dual coding.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1wfnleqsqvat2"
    },
    {
      "id": "ot-load-sweller-1",
      "shape": "mcq",
      "tags": [
        "cognitive load",
        "Sweller",
        "attribution"
      ],
      "prompt": {
        "modality": "text",
        "value": "Cognitive Load Theory — that working memory's limited capacity must be managed by instruction — was proposed by whom, and when?"
      },
      "options": [
        {
          "modality": "text",
          "value": "John Sweller, 1988"
        },
        {
          "modality": "text",
          "value": "Allan Paivio, 1971"
        },
        {
          "modality": "text",
          "value": "Robert Gagné, 1965"
        },
        {
          "modality": "text",
          "value": "George Miller, 1956"
        }
      ],
      "correctIndex": 0,
      "explanation": "Sweller advanced Cognitive Load Theory in 1988, building on the working-memory limit George Miller had quantified in 1956. Paivio's 1971 work is Dual Coding Theory, and Gagné's 1965 Conditions of Learning is an instructional-design framework.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1335czh8vbrh3"
    },
    {
      "id": "ot-load-wm-2",
      "shape": "mcq",
      "tags": [
        "cognitive load",
        "working memory"
      ],
      "prompt": {
        "modality": "text",
        "value": "Roughly how many items can working memory hold at once, per Cognitive Load Theory?"
      },
      "options": [
        {
          "modality": "text",
          "value": "20"
        },
        {
          "modality": "text",
          "value": "12"
        },
        {
          "modality": "text",
          "value": "7"
        },
        {
          "modality": "text",
          "value": "3"
        }
      ],
      "correctIndex": 2,
      "explanation": "The classic estimate is about 7 items — small enough that instruction must actively manage load, which is the theory's central practical claim.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1nvxwqv98t2gt"
    },
    {
      "id": "ot-load-extraneous-3",
      "shape": "mcq",
      "tags": [
        "cognitive load",
        "extraneous",
        "application"
      ],
      "prompt": {
        "modality": "text",
        "value": "A slide is crammed with decorative animations and off-topic text that make the point harder to find. Which kind of cognitive load has the designer added?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Extraneous load"
        },
        {
          "modality": "text",
          "value": "Germane load"
        },
        {
          "modality": "text",
          "value": "Intrinsic load"
        },
        {
          "modality": "text",
          "value": "Perceptual load"
        }
      ],
      "correctIndex": 0,
      "explanation": "Extraneous load is unnecessary complexity created by poor instructional design, and should be eliminated. Germane load is the productive effort of schema building, intrinsic load is set by the topic, and perceptual load is an attention-research term, not one of CLT's three types.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1ayjvpk12wgbe8"
    },
    {
      "id": "ot-load-intrinsic-4",
      "shape": "mcq",
      "tags": [
        "cognitive load",
        "intrinsic",
        "compare"
      ],
      "prompt": {
        "modality": "text",
        "value": "In Cognitive Load Theory, what sets the amount of intrinsic load a topic carries?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The quality of the instructional design",
          "short": "Instructional design quality"
        },
        {
          "modality": "text",
          "value": "The effort a learner spends building schemas",
          "short": "Learner's schema-building effort"
        },
        {
          "modality": "text",
          "value": "The inherent complexity of the material",
          "short": "The material's own complexity"
        },
        {
          "modality": "text",
          "value": "The capacity of the learner's working memory",
          "short": "Learner's working-memory capacity"
        }
      ],
      "correctIndex": 2,
      "explanation": "Intrinsic load comes from the inherent complexity of the material: it is set by the topic and cannot be designed away. Design quality governs extraneous load, schema-building effort is germane load, and working memory's limits are why load must be managed, not what sets it.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "pexh1z1pq037x"
    },
    {
      "id": "ot-connectivism-authors-1",
      "shape": "mcq",
      "tags": [
        "connectivism",
        "attribution"
      ],
      "prompt": {
        "modality": "text",
        "value": "Connectivism, 'the learning theory for the digital age,' was developed by which pair, and in what year?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Gagné & Briggs, 1965"
        },
        {
          "modality": "text",
          "value": "Siemens & Downes, 2004"
        },
        {
          "modality": "text",
          "value": "Anderson & Krathwohl, 2001"
        },
        {
          "modality": "text",
          "value": "Sweller & Chandler, 1988"
        }
      ],
      "correctIndex": 1,
      "explanation": "George Siemens and Stephen Downes developed connectivism in 2004–05, starting from Siemens's 2004 paper. Anderson and Krathwohl's 2001 revision of Bloom's taxonomy, Gagné's 1965 Conditions of Learning and Sweller's 1988 load theory all predate the network framing.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "15ol5up1w3fbjv"
    },
    {
      "id": "ot-udl-not-1",
      "shape": "mcq",
      "tags": [
        "UDL",
        "principles"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which of these is NOT one of UDL's three principles?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Action & Expression"
        },
        {
          "modality": "text",
          "value": "Representation"
        },
        {
          "modality": "text",
          "value": "Reinforcement"
        },
        {
          "modality": "text",
          "value": "Engagement"
        }
      ],
      "correctIndex": 2,
      "explanation": "UDL's three principles are Representation (the what), Action & Expression (the how), and Engagement (the why). Reinforcement belongs to behaviorism, not UDL.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1xa0szo11l2igk"
    },
    {
      "id": "ot-keyword-method-2",
      "shape": "mcq",
      "tags": [
        "keyword method",
        "mnemonics"
      ],
      "prompt": {
        "modality": "text",
        "value": "What does the Keyword Method have a learner do?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Match a task's difficulty to the learner's current skill so focus holds",
          "short": "Match difficulty to skill level"
        },
        {
          "modality": "text",
          "value": "Link a foreign word's sound to an image that bridges to its translation",
          "short": "Link a word's sound to an image"
        },
        {
          "modality": "text",
          "value": "Group a long list of words into a few meaningful units so working memory copes",
          "short": "Group words into meaningful units"
        },
        {
          "modality": "text",
          "value": "Place each item at a spot along a familiar mental route and walk it to recall",
          "short": "Place items along a mental route"
        }
      ],
      "correctIndex": 1,
      "explanation": "The Keyword Method is a language mnemonic — e.g. picturing a four (quatre) on a fork for fourchette. Placing items along a route is the Method of Loci, a different technique.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "y583jqbmymoy"
    },
    {
      "id": "ot-loci-origin-3",
      "shape": "mcq",
      "tags": [
        "method of loci",
        "history"
      ],
      "prompt": {
        "modality": "text",
        "value": "Where did the Method of Loci (Memory Palace) originate?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Ancient Egypt and Persia"
        },
        {
          "modality": "text",
          "value": "Ancient Greece and Rome"
        },
        {
          "modality": "text",
          "value": "Ancient India and China"
        },
        {
          "modality": "text",
          "value": "Ancient Babylon and Assyria"
        }
      ],
      "correctIndex": 1,
      "explanation": "The Method of Loci comes from ancient Greece and Rome, where orators used it to hold long speeches in sequence. It long predates the Renaissance revival of the technique.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "bm9bsvv3v60l"
    },
    {
      "id": "ot-addie-phases-1",
      "shape": "mcq",
      "tags": [
        "addie",
        "origin"
      ],
      "prompt": {
        "modality": "text",
        "value": "Where and in what year was ADDIE developed?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Syracuse University's Center for Instructional Development, 1972",
          "short": "Syracuse Univ., 1972"
        },
        {
          "modality": "text",
          "value": "Indiana University's Department of Instructional Systems Technology, 1978",
          "short": "Indiana Univ., 1978"
        },
        {
          "modality": "text",
          "value": "University of Pittsburgh's Learning Research and Development Center, 1985",
          "short": "Univ. of Pittsburgh, 1985"
        },
        {
          "modality": "text",
          "value": "Florida State University's Center for Educational Technology, 1975",
          "short": "Florida State Univ., 1975"
        }
      ],
      "correctIndex": 3,
      "explanation": "ADDIE was developed in 1975 at Florida State University's Center for Educational Technology. 1978 is the Dick & Carey Model's date, not ADDIE's.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1kg3v1119ti7"
    },
    {
      "id": "ot-addie-phases-2",
      "shape": "mcq",
      "tags": [
        "addie",
        "origin"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which organization commissioned the work that produced ADDIE?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The U.S. Navy"
        },
        {
          "modality": "text",
          "value": "The U.S. Army"
        },
        {
          "modality": "text",
          "value": "The Air Force"
        },
        {
          "modality": "text",
          "value": "The Marine Corps"
        }
      ],
      "correctIndex": 1,
      "explanation": "The U.S. Army commissioned ADDIE to bring engineering-style rigor to training production. The other services were not the commissioning body.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1f7q0t0159cc7o"
    },
    {
      "id": "ot-addie-phases-3",
      "shape": "mcq",
      "tags": [
        "addie",
        "phases"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which ADDIE phase is where you identify goals, audience, prior knowledge, and constraints?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Develop"
        },
        {
          "modality": "text",
          "value": "Design"
        },
        {
          "modality": "text",
          "value": "Implement"
        },
        {
          "modality": "text",
          "value": "Analyze"
        }
      ],
      "correctIndex": 3,
      "explanation": "Analyze is the front-end phase that establishes goals, audience, prior knowledge, and constraints. Design comes next and instead defines objectives, assessment, and sequencing.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1aerrj7xlvlqp"
    },
    {
      "id": "ot-addie-phases-4",
      "shape": "mcq",
      "tags": [
        "addie",
        "phases"
      ],
      "prompt": {
        "modality": "text",
        "value": "A team has just finished ADDIE's Analyze phase. Which phase comes next, and what does it involve?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Develop — define objectives, assessment strategy, sequencing, and modalities",
          "short": "Develop — define objectives & strategy"
        },
        {
          "modality": "text",
          "value": "Design — produce the content, activities, and assessments",
          "short": "Design — build content & assessments"
        },
        {
          "modality": "text",
          "value": "Develop — produce the content, activities, and assessments",
          "short": "Develop — build content & assessments"
        },
        {
          "modality": "text",
          "value": "Design — define objectives, assessment strategy, sequencing, and modalities",
          "short": "Design — define objectives & strategy"
        }
      ],
      "correctIndex": 3,
      "explanation": "Design follows Analyze, and it is where objectives, assessment strategy, sequencing, and modalities are set. Producing the actual content is Develop, the phase after Design.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "jw5ndx1ecllf3"
    },
    {
      "id": "ot-addie-phases-5",
      "shape": "mcq",
      "tags": [
        "addie",
        "phases"
      ],
      "prompt": {
        "modality": "text",
        "value": "A team has finished planning objectives and sequencing, and is now producing the actual videos, activities, and quiz items. Which ADDIE phase is this?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Implement"
        },
        {
          "modality": "text",
          "value": "Design"
        },
        {
          "modality": "text",
          "value": "Analyze"
        },
        {
          "modality": "text",
          "value": "Develop"
        }
      ],
      "correctIndex": 3,
      "explanation": "Develop is the build phase — producing the content, activities, and assessments. Implement would be delivering that finished material to learners.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "17s2wwiblccg6"
    },
    {
      "id": "ot-addie-eval-1",
      "shape": "mcq",
      "tags": [
        "addie",
        "evaluate"
      ],
      "prompt": {
        "modality": "text",
        "value": "What is the main benefit of running ADDIE's Evaluate phase continuously?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Learner delivery starts earlier rather than after the build phase"
        },
        {
          "modality": "text",
          "value": "Thorough documentation becomes optional rather than required"
        },
        {
          "modality": "text",
          "value": "Design flaws surface early rather than after delivery"
        },
        {
          "modality": "text",
          "value": "The five phases blend into one cycle rather than a sequence"
        }
      ],
      "correctIndex": 2,
      "explanation": "Continuous evaluation catches problems while they are still cheap to fix, instead of waiting until learners have already received the course. It does not merge or reorder the other four phases, and it does not lighten the documentation ADDIE is valued for.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "8kjko28bq93i"
    },
    {
      "id": "ot-addie-eval-2",
      "shape": "mcq",
      "tags": [
        "addie",
        "evaluate"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which of ADDIE's five phases is described as the continuous quality check rather than a discrete step?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Analyze"
        },
        {
          "modality": "text",
          "value": "Implement"
        },
        {
          "modality": "text",
          "value": "Evaluate"
        },
        {
          "modality": "text",
          "value": "Develop"
        }
      ],
      "correctIndex": 2,
      "explanation": "Evaluate is ADDIE's continuous quality check — it threads through the other phases instead of running once. Implement, by contrast, is the discrete delivery step.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "51n89vjc0ipd"
    },
    {
      "id": "ot-addie-eval-3",
      "shape": "mcq",
      "tags": [
        "addie",
        "evaluate"
      ],
      "prompt": {
        "modality": "text",
        "value": "A team builds a full course and collects no feedback of any kind until after launch day. Which ADDIE principle did they violate?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Analyze should repeat at the end of every phase, not run once up front",
          "short": "Analyze repeats after every phase"
        },
        {
          "modality": "text",
          "value": "Evaluate should thread through every phase, not act as a final gate",
          "short": "Evaluate runs through every phase"
        },
        {
          "modality": "text",
          "value": "Develop should begin before objectives are set, not wait for Design",
          "short": "Develop starts before Design"
        },
        {
          "modality": "text",
          "value": "Implement should run as a continuous loop, not as a discrete delivery step",
          "short": "Implement runs as a continuous loop"
        }
      ],
      "correctIndex": 1,
      "explanation": "Deferring all feedback to after launch treats Evaluate as a final gate, which is exactly what ADDIE says it is not. The other options are not ADDIE principles at all: Analyze runs once up front, Develop waits for Design's objectives, and Implement is the discrete delivery step.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1tatunc1d3yfh4"
    },
    {
      "id": "ot-addie-eval-4",
      "shape": "mcq",
      "tags": [
        "addie",
        "evaluate"
      ],
      "prompt": {
        "modality": "text",
        "value": "How does ADDIE's Evaluate differ from a conventional final quality gate?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It is front-loaded, scoping audience and constraints before any design",
          "short": "Front-loaded, scopes work first"
        },
        {
          "modality": "text",
          "value": "It is continuous, feeding findings back into the earlier phases",
          "short": "Continuous, loops back to phases"
        },
        {
          "modality": "text",
          "value": "It is prototype-led, testing rough drafts with learners before the build",
          "short": "Prototype-led, tests drafts early"
        },
        {
          "modality": "text",
          "value": "It is cumulative, carrying its findings forward into the next project",
          "short": "Cumulative, informs next project"
        }
      ],
      "correctIndex": 1,
      "explanation": "A final gate runs once at the end; ADDIE's Evaluate runs throughout and returns findings to earlier phases of the same project. It is not a one-off front-end step, and it is not limited to compliance work.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "11kcamrewyqg9"
    },
    {
      "id": "ot-frameworks-1",
      "shape": "mcq",
      "tags": [
        "sam",
        "frameworks"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which framework is defined by rapid, agile prototyping and explicitly iterative cycles?"
      },
      "options": [
        {
          "modality": "text",
          "value": "UbD (1998)"
        },
        {
          "modality": "text",
          "value": "ADDIE (1975)"
        },
        {
          "modality": "text",
          "value": "ARCS (1987)"
        },
        {
          "modality": "text",
          "value": "SAM (2012)"
        }
      ],
      "correctIndex": 3,
      "explanation": "SAM, Michael Allen's Successive Approximation Model, is the iterative counterpoint to ADDIE, built on rapid prototyping and short revision cycles.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1l48pbk71ty0"
    },
    {
      "id": "ot-frameworks-2",
      "shape": "mcq",
      "tags": [
        "merrill",
        "frameworks"
      ],
      "prompt": {
        "modality": "text",
        "value": "Merrill's Principles of Instruction (2002) is best described as which of the following?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Performance-focused design that strips out 'nice to know' content"
        },
        {
          "modality": "text",
          "value": "Systems-based view of instruction as interacting components"
        },
        {
          "modality": "text",
          "value": "Task-centered 'first principles' of effective design"
        },
        {
          "modality": "text",
          "value": "Prototype-driven process built on rapid, short revision cycles"
        }
      ],
      "correctIndex": 2,
      "explanation": "Merrill's Principles are task-centered 'first principles' — problem-centered, activation, demonstration, application, integration. The nine-component systems view is Dick & Carey.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "tfphlx1u4taan"
    },
    {
      "id": "ot-frameworks-3",
      "shape": "mcq",
      "tags": [
        "dick-carey",
        "frameworks"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which framework treats instruction as nine interacting components rather than a set of phases?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Understanding by Design"
        },
        {
          "modality": "text",
          "value": "Merrill's Principles"
        },
        {
          "modality": "text",
          "value": "Moore's Action Mapping"
        },
        {
          "modality": "text",
          "value": "Dick & Carey Model"
        }
      ],
      "correctIndex": 3,
      "explanation": "The Dick & Carey Model (1978) takes a systems view of instruction as nine interacting components, and is more prescriptive than ADDIE.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "14u4qu7178w3jh"
    },
    {
      "id": "ot-frameworks-4",
      "shape": "mcq",
      "tags": [
        "ubd",
        "frameworks"
      ],
      "prompt": {
        "modality": "text",
        "value": "A team wants to begin from the outcomes learners should achieve, then work back to assessments and only then to instruction. Which framework fits?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Successive Approximation Model"
        },
        {
          "modality": "text",
          "value": "Dick and Carey Model"
        },
        {
          "modality": "text",
          "value": "Understanding by Design"
        },
        {
          "modality": "text",
          "value": "Merrill's First Principles"
        }
      ],
      "correctIndex": 2,
      "explanation": "Understanding by Design (1998) is built on exactly this outcome-first, work-backward sequence. The Successive Approximation Model (SAM) would instead push them toward early prototyping.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "pzrwgnlqjwr1"
    },
    {
      "id": "ot-frameworks-5",
      "shape": "mcq",
      "tags": [
        "frameworks",
        "matching"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which framework-to-approach pairing is NOT correct?"
      },
      "options": [
        {
          "modality": "text",
          "value": "SAM (2012) — a linear, phase-by-phase process built for thorough documentation",
          "short": "SAM: linear, documentation-heavy"
        },
        {
          "modality": "text",
          "value": "Dick & Carey Model (1978) — a systems process built from nine interacting components",
          "short": "Dick & Carey: nine-component systems process"
        },
        {
          "modality": "text",
          "value": "Understanding by Design (1998) — a backward-design process built back from desired outcomes",
          "short": "UbD: backward design from outcomes"
        },
        {
          "modality": "text",
          "value": "Merrill's Principles (2002) — a task-centered process built on first principles of effective design",
          "short": "Merrill: task-centered first principles"
        }
      ],
      "correctIndex": 0,
      "explanation": "SAM is rapid, agile, explicitly iterative prototyping; the linear, documentation-heavy description belongs to ADDIE, the model SAM was built as a counterpoint to.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1ip45wr1975x3l"
    },
    {
      "id": "ot-backward-action-1",
      "shape": "mcq",
      "tags": [
        "action-mapping",
        "attribution"
      ],
      "prompt": {
        "modality": "text",
        "value": "Action Mapping (2008) is the work of which designer?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Grant Wiggins"
        },
        {
          "modality": "text",
          "value": "Michael Allen"
        },
        {
          "modality": "text",
          "value": "Robert Gagné"
        },
        {
          "modality": "text",
          "value": "Cathy Moore"
        }
      ],
      "correctIndex": 3,
      "explanation": "Action Mapping is Cathy Moore's performance-focused method. Michael Allen created SAM, Grant Wiggins co-created Understanding by Design with Jay McTighe, and Robert Gagné's contribution is the Nine Events of Instruction.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1d2vc331wex23p"
    },
    {
      "id": "ot-backward-action-2",
      "shape": "mcq",
      "tags": [
        "action-mapping",
        "frameworks"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which describes Action Mapping's defining move?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Strip out 'nice to know' content and design around what learners must do on the job",
          "short": "Design around on-the-job actions"
        },
        {
          "modality": "text",
          "value": "Build every lesson on task-centered 'first principles' of effective design",
          "short": "Build on task-centered first principles"
        },
        {
          "modality": "text",
          "value": "Start from desired learning outcomes and work 'backward' to assessments, then instruction",
          "short": "Work back from desired outcomes"
        },
        {
          "modality": "text",
          "value": "Cycle through 'successive approximations' of a prototype in short, repeated loops",
          "short": "Cycle prototypes in short loops"
        }
      ],
      "correctIndex": 0,
      "explanation": "Action Mapping is performance-focused: cut the 'nice to know' and design around real on-the-job actions. Starting from outcomes and working back is backward design (UbD); task-centered first principles are Merrill's; successive-approximation prototype loops are SAM's.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1cef31z1lsys8l"
    },
    {
      "id": "ot-backward-action-3",
      "shape": "mcq",
      "tags": [
        "backward-design",
        "ubd"
      ],
      "prompt": {
        "modality": "text",
        "value": "A designer names the outcomes learners should achieve, then writes the assessments that would prove them, then plans the lessons. Which approach is this?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Performance-led design"
        },
        {
          "modality": "text",
          "value": "Task-centered design"
        },
        {
          "modality": "text",
          "value": "Backward design"
        },
        {
          "modality": "text",
          "value": "Prototype-led design"
        }
      ],
      "correctIndex": 2,
      "explanation": "This outcomes → assessments → instruction order is backward design, from Wiggins and McTighe's Understanding by Design. Performance-focused design (Action Mapping) would instead start from required on-the-job performance; task-centered design is Merrill's and rapid prototyping is SAM's.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1y1j1h41qdbak0"
    },
    {
      "id": "ot-backward-action-4",
      "shape": "mcq",
      "tags": [
        "backward-design",
        "action-mapping"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which statement correctly distinguishes the two approaches?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Backward design starts from rapid prototypes; Action Mapping starts from nine interacting components",
          "short": "Backward: prototypes; Action Mapping: components"
        },
        {
          "modality": "text",
          "value": "Backward design starts from desired learning outcomes; Action Mapping starts from on-the-job performance",
          "short": "Backward: outcomes; Action Mapping: job performance"
        },
        {
          "modality": "text",
          "value": "Backward design starts from on-the-job performance; Action Mapping starts from desired learning outcomes",
          "short": "Backward: job performance; Action Mapping: outcomes"
        },
        {
          "modality": "text",
          "value": "Backward design starts from nine interacting components; Action Mapping starts from rapid prototypes",
          "short": "Backward: components; Action Mapping: prototypes"
        }
      ],
      "correctIndex": 1,
      "explanation": "Backward design (Wiggins & McTighe, UbD 1998) works back from desired learning outcomes; Action Mapping (Cathy Moore, 2008) starts from required on-the-job performance.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "omti421stntq"
    },
    {
      "id": "ot-socratic-1",
      "shape": "mcq",
      "tags": [
        "socratic",
        "definition"
      ],
      "prompt": {
        "modality": "text",
        "value": "The Socratic method teaches primarily by which means?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Strategic questions that make learners surface and examine their own reasoning",
          "short": "Questions that probe your reasoning"
        },
        {
          "modality": "text",
          "value": "Reflective journals in which learners record and revisit their own reasoning",
          "short": "Journals that revisit your reasoning"
        },
        {
          "modality": "text",
          "value": "Worked examples that model expert reasoning before learners attempt their own",
          "short": "Worked examples that model reasoning"
        },
        {
          "modality": "text",
          "value": "Collaborative projects in which learners negotiate a shared interpretation",
          "short": "Projects that build a shared reading"
        }
      ],
      "correctIndex": 0,
      "explanation": "The Socratic method is teaching through probing questions so learners reach the insight themselves. Journals, worked examples and group projects are other ways to engage reasoning, but none is the Socratic method's means.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "3kxq0szj2sxg"
    },
    {
      "id": "ot-socratic-2",
      "shape": "mcq",
      "tags": [
        "khanmigo",
        "attribution"
      ],
      "prompt": {
        "modality": "text",
        "value": "Who built Khanmigo to operationalize Socratic principles at scale?"
      },
      "options": [
        {
          "modality": "text",
          "value": "John Warner"
        },
        {
          "modality": "text",
          "value": "David Rose"
        },
        {
          "modality": "text",
          "value": "Nick Pelling"
        },
        {
          "modality": "text",
          "value": "Sal Khan"
        }
      ],
      "correctIndex": 3,
      "explanation": "Sal Khan built Khanmigo. Chrisman Frank founded Synthesis, a rival AI tutor; Stephen Downes co-developed connectivism; John Warner is the critic who reviewed Brave New Words.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1l8ljy9tckr6b"
    },
    {
      "id": "ot-socratic-3",
      "shape": "mcq",
      "tags": [
        "khanmigo",
        "socratic"
      ],
      "prompt": {
        "modality": "text",
        "value": "How is Khanmigo designed to respond when a student is stuck on a problem?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Show the worked solution, then let them retry it unaided",
          "short": "Show the solution, then let them retry"
        },
        {
          "modality": "text",
          "value": "Let them pick a hint, an example, or the full answer",
          "short": "Let them pick hint, example, or answer"
        },
        {
          "modality": "text",
          "value": "Set a similar problem for them to attempt on their own",
          "short": "Set a similar problem to try alone"
        },
        {
          "modality": "text",
          "value": "Guide them through it with probing questions",
          "short": "Guide them with probing questions"
        }
      ],
      "correctIndex": 3,
      "explanation": "Khanmigo guides students through problems with probing questions rather than surfacing the answer — that is the Socratic design choice. Walking them through a worked solution, swapping in an easier task or re-explaining the concept all hand over what the guide says it withholds.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1b1tcdmvl47q"
    },
    {
      "id": "ot-socratic-4",
      "shape": "mcq",
      "tags": [
        "khanmigo",
        "constructivism"
      ],
      "prompt": {
        "modality": "text",
        "value": "Khanmigo's question-first design reflects which constructivist finding?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Giving answers immediately lowers cognitive load and so improves retention",
          "short": "Instant answers lower load, aiding retention"
        },
        {
          "modality": "text",
          "value": "Knowledge constructed through guided questioning encodes more durably than knowledge merely received",
          "short": "Knowledge built via questioning sticks better"
        },
        {
          "modality": "text",
          "value": "Learners retain more when content matches their preferred modality",
          "short": "Retention rises when content fits your modality"
        },
        {
          "modality": "text",
          "value": "Retention depends mainly on total time spent on task",
          "short": "Retention depends mainly on time on task"
        }
      ],
      "correctIndex": 1,
      "explanation": "The design rests on the finding that knowledge a learner constructs through guided questioning encodes more durably than knowledge simply handed over. Modality preference is not the supported claim here.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "11ou6ggml3hhs"
    },
    {
      "id": "ot-socratic-5",
      "shape": "mcq",
      "tags": [
        "socratic",
        "definition"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which is NOT characteristic of the Socratic method?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Pressing the learner with a run of pointed, strategic questions",
          "short": "Pressing learners with pointed questions"
        },
        {
          "modality": "text",
          "value": "Forcing the learner to expose the gaps in their own reasoning",
          "short": "Forcing learners to expose reasoning gaps"
        },
        {
          "modality": "text",
          "value": "Delivering the conclusion directly so the learner can memorize it",
          "short": "Delivering the conclusion to memorize"
        },
        {
          "modality": "text",
          "value": "Making the learner reach the insight through their own effort",
          "short": "Making learners reach insight themselves"
        }
      ],
      "correctIndex": 2,
      "explanation": "Handing over the conclusion is the opposite of the Socratic method, which presses the learner with questions, forces them to examine their own reasoning and leaves them to reach the insight themselves.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1sbjx0y1jhua32"
    },
    {
      "id": "ot-personalization-1",
      "shape": "mcq",
      "tags": [
        "personalization",
        "tutoring"
      ],
      "prompt": {
        "modality": "text",
        "value": "According to Khan, what four things must an effective tutor understand about a learner?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Their IQ, learning style, family income, and career goals",
          "short": "IQ, learning style, income, career goals"
        },
        {
          "modality": "text",
          "value": "Where they are, what they know, how they learn, and what engages them",
          "short": "Level, knowledge, how they learn, engagement"
        },
        {
          "modality": "text",
          "value": "Their grade level, test scores, attendance, and school district",
          "short": "Grade, test scores, attendance, district"
        },
        {
          "modality": "text",
          "value": "Their reading speed, memory span, motivation, and screen time",
          "short": "Reading speed, memory, motivation, screen time"
        }
      ],
      "correctIndex": 1,
      "explanation": "The personalization problem is defined as understanding where a specific learner is, what they know, how they learn, and what engages them. The other options list demographic or diagnostic data, not the four dimensions Khan names.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1dckd8r17htle1"
    },
    {
      "id": "ot-personalization-2",
      "shape": "mcq",
      "tags": [
        "personalization",
        "equity"
      ],
      "prompt": {
        "modality": "text",
        "value": "Historically, why has the personalization problem gone unsolved for most students?"
      },
      "options": [
        {
          "modality": "text",
          "value": "That level of individual attention exceeded what even wealthy families could buy",
          "short": "Beyond even wealthy families' reach"
        },
        {
          "modality": "text",
          "value": "That level of individual attention required expensive private tutors",
          "short": "Individual attention needs costly tutors"
        },
        {
          "modality": "text",
          "value": "That level of individual attention was cheap but confined to elite boarding schools",
          "short": "Cheap but confined to elite boarding schools"
        },
        {
          "modality": "text",
          "value": "That level of individual attention arrived only with adaptive software",
          "short": "Arrived only with adaptive software"
        }
      ],
      "correctIndex": 1,
      "explanation": "Khan's framing is economic: understanding each learner individually was historically only possible with expensive private tutoring, which wealthy families could buy and under-resourced students could not.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1pb7n93llao7"
    },
    {
      "id": "ot-personalization-3",
      "shape": "mcq",
      "tags": [
        "2-sigma",
        "bloom"
      ],
      "prompt": {
        "modality": "text",
        "value": "Benjamin Bloom's 1984 finding, which Khan invokes, showed individually tutored students outperform classroom peers by how much?"
      },
      "options": [
        {
          "modality": "text",
          "value": "One standard deviation"
        },
        {
          "modality": "text",
          "value": "Three standard deviations"
        },
        {
          "modality": "text",
          "value": "Two standard deviations"
        },
        {
          "modality": "text",
          "value": "Half a standard deviation"
        }
      ],
      "correctIndex": 2,
      "explanation": "Bloom's 2 Sigma Problem (1984) found a two-standard-deviation advantage for tutored students — the gap Khan argues AI can finally close at scale. Mastery learning alone reached about one sigma in Bloom's comparison, and nothing in his ranking of alterable variables came near three.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1asna3i1dzo6my"
    },
    {
      "id": "ot-personalization-4",
      "shape": "mcq",
      "tags": [
        "personalization",
        "teachers"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which is NOT part of Khan's argument about AI and the personalization problem?"
      },
      "options": [
        {
          "modality": "text",
          "value": "AI can make individualized tutoring free and ubiquitous",
          "short": "AI can make tutoring free and ubiquitous"
        },
        {
          "modality": "text",
          "value": "The tutoring gap is an equity problem, not a minor inefficiency",
          "short": "The tutoring gap is an equity problem"
        },
        {
          "modality": "text",
          "value": "AI tutoring should replace the teacher's professional judgment",
          "short": "AI should replace teachers' judgment"
        },
        {
          "modality": "text",
          "value": "AI can fill the unsupported hours between classes",
          "short": "AI can fill unsupported hours between classes"
        }
      ],
      "correctIndex": 2,
      "explanation": "Khan explicitly says the technology does not replace the teacher's judgment; it fills the hours between classes. The other three are claims the book makes directly.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "8byk4b165qog1"
    },
    {
      "id": "ot-personalization-5",
      "shape": "mcq",
      "tags": [
        "personalization",
        "equity",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "A district gives every student 24/7 access to an AI tutor that adapts to their pace. In Khan's framing, this most directly attacks which problem?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The gap between what schools teach and what employers later need"
        },
        {
          "modality": "text",
          "value": "The gap between what learners know and what tests can measure"
        },
        {
          "modality": "text",
          "value": "The gap between what tutored and classroom learners achieve"
        },
        {
          "modality": "text",
          "value": "The gap between what parents expect and what schools report home"
        }
      ],
      "correctIndex": 2,
      "explanation": "This is Bloom's 2 Sigma gap — the tutoring advantage no systemic intervention has closed at scale. Khan frames free, ubiquitous tutoring as the first credible answer to it; the other gaps are real complaints about schooling, but none is the one Bloom measured.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "jiecnp1srmx3j"
    },
    {
      "id": "ot-scifi-1",
      "shape": "mcq",
      "tags": [
        "diamond-age",
        "inspirations"
      ],
      "prompt": {
        "modality": "text",
        "value": "In Neal Stephenson's The Diamond Age, what educational vision inspired Khan?"
      },
      "options": [
        {
          "modality": "text",
          "value": "A shared virtual classroom lets children from every district learn together",
          "short": "A virtual classroom for every district"
        },
        {
          "modality": "text",
          "value": "A gifted boy hones his strategic talent through escalating simulated battles",
          "short": "A gifted boy trained by simulated battles"
        },
        {
          "modality": "text",
          "value": "An AI tutor becomes a poor girl's greatest educational resource",
          "short": "An AI tutor is a poor girl's key resource"
        },
        {
          "modality": "text",
          "value": "A girl schooled by a machine at home marvels at the idea of a classroom",
          "short": "A machine-schooled girl marvels at classrooms"
        }
      ],
      "correctIndex": 2,
      "explanation": "The Diamond Age features an AI tutor that transforms a poor girl's life — the equity vision at the heart of Khan's argument. The simulated-battle and marvelling-at-a-classroom visions belong to Ender's Game and 'The Fun They Had'; a shared virtual classroom appears in none of the three.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "5n3lng1axuiec"
    },
    {
      "id": "ot-scifi-2",
      "shape": "mcq",
      "tags": [
        "enders-game",
        "inspirations"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which work supplies Khan's image of personalized, challenge-driven simulation learning?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The Diamond Age"
        },
        {
          "modality": "text",
          "value": "Ender's Game"
        },
        {
          "modality": "text",
          "value": "Snow Crash"
        },
        {
          "modality": "text",
          "value": "\"The Fun They Had\""
        }
      ],
      "correctIndex": 1,
      "explanation": "Ender's Game supplies the challenge-driven simulation model. The Diamond Age supplies the AI-tutor-as-equalizer image, and 'The Fun They Had' the exotic-classroom image; Snow Crash is not a touchstone at all.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1663rliws8bv6"
    },
    {
      "id": "ot-scifi-3",
      "shape": "mcq",
      "tags": [
        "asimov",
        "inspirations"
      ],
      "prompt": {
        "modality": "text",
        "value": "Asimov's \"The Fun They Had\" contributes which idea to Khan's opening?"
      },
      "options": [
        {
          "modality": "text",
          "value": "A future child is lifted from poverty by a machine tutor"
        },
        {
          "modality": "text",
          "value": "A future child attends a school built inside a shared virtual world"
        },
        {
          "modality": "text",
          "value": "A future child finds a gift for command through simulated battles"
        },
        {
          "modality": "text",
          "value": "A future child finds a classroom of other children exotic"
        }
      ],
      "correctIndex": 3,
      "explanation": "Asimov's story imagines a future child for whom a room full of peers is an exotic concept. The rescue-from-poverty and battle-simulation ideas come from The Diamond Age and Ender's Game; the virtual-world school belongs to none of Khan's three touchstones.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "15j775oqswh5g"
    },
    {
      "id": "ot-scifi-4",
      "shape": "mcq",
      "tags": [
        "inspirations",
        "synthesis"
      ],
      "prompt": {
        "modality": "text",
        "value": "What do all three of Khan's literary touchstones have in common?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Each imagines personalized, adaptive instruction available to any child",
          "short": "Each imagines adaptive tutoring for all"
        },
        {
          "modality": "text",
          "value": "Each imagines a child's gifts drawn out by a devoted human mentor",
          "short": "Each has a devoted human mentor"
        },
        {
          "modality": "text",
          "value": "Each imagines instruction that a whole community shapes together",
          "short": "Each has community-shaped instruction"
        },
        {
          "modality": "text",
          "value": "Each imagines adaptive instruction tuned to a whole class rather than one child",
          "short": "Each tunes instruction to a whole class"
        }
      ],
      "correctIndex": 0,
      "explanation": "Khan opens with three works of speculative fiction that each imagine personalized, adaptive instruction regardless of wealth. Two of the three put a machine rather than a human mentor at the centre, and each follows a single child rather than a class or a community.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "o4qy411xmqc3"
    },
    {
      "id": "ot-khanmigo-1",
      "shape": "mcq",
      "tags": [
        "khanmigo",
        "conmigo"
      ],
      "prompt": {
        "modality": "text",
        "value": "Khanmigo's name fuses \"Khan\" with a Spanish word meaning what?"
      },
      "options": [
        {
          "modality": "text",
          "value": "\"Teach me\""
        },
        {
          "modality": "text",
          "value": "\"My friend\""
        },
        {
          "modality": "text",
          "value": "\"With me\""
        },
        {
          "modality": "text",
          "value": "\"Come along\""
        }
      ],
      "correctIndex": 2,
      "explanation": "The pun is on conmigo, Spanish for 'with me' — encoding a tutor that accompanies rather than lectures. The other glosses are plausible Spanish-sounding readings but not what conmigo means.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "3koz2nhiurgt"
    },
    {
      "id": "ot-khanmigo-2",
      "shape": "mcq",
      "tags": [
        "khanmigo",
        "gpt-4"
      ],
      "prompt": {
        "modality": "text",
        "value": "Khanmigo was built on which model, and with which partner?"
      },
      "options": [
        {
          "modality": "text",
          "value": "GPT-4, in partnership with Google"
        },
        {
          "modality": "text",
          "value": "Gemini, in partnership with Google"
        },
        {
          "modality": "text",
          "value": "Gemini, in partnership with OpenAI"
        },
        {
          "modality": "text",
          "value": "GPT-4, in partnership with OpenAI"
        }
      ],
      "correctIndex": 3,
      "explanation": "Khanmigo is built on GPT-4 in collaboration with OpenAI, serving as Khan Academy's proof of concept for the book's thesis.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1p126571gt46vt"
    },
    {
      "id": "ot-khanmigo-3",
      "shape": "mcq",
      "tags": [
        "khanmigo",
        "socratic"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which teaching method does Khanmigo use by design?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The flipped classroom — assigning lessons at home and problems in class",
          "short": "Flipped classroom — lessons at home"
        },
        {
          "modality": "text",
          "value": "Direct instruction — modelling answers through worked examples",
          "short": "Direct instruction — modelled examples"
        },
        {
          "modality": "text",
          "value": "Anki-style spaced repetition — scheduling each review at an expanding interval",
          "short": "Spaced repetition — expanding intervals"
        },
        {
          "modality": "text",
          "value": "The Socratic method — guiding toward answers through questions",
          "short": "Socratic method — guiding via questions"
        }
      ],
      "correctIndex": 3,
      "explanation": "Khanmigo guides students toward answers via Socratic dialogue and never simply delivers them. Direct instruction is closest to what the design deliberately avoids; the flipped classroom is a Khan Academy association, not the tutor's method.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "b2x4e3oqzjbl"
    },
    {
      "id": "ot-khanmigo-4",
      "shape": "mcq",
      "tags": [
        "khanmigo",
        "pedagogy"
      ],
      "prompt": {
        "modality": "text",
        "value": "Why does Khanmigo deliberately refuse to hand students the answer on demand?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It would undermine the productive struggle that makes learning stick",
          "short": "It undermines the productive struggle"
        },
        {
          "modality": "text",
          "value": "It would deprive the teacher of the correction that fixes a misconception",
          "short": "It deprives the teacher of the correction"
        },
        {
          "modality": "text",
          "value": "It would push students past the pace that their mastery data supports",
          "short": "It pushes students past their mastery pace"
        },
        {
          "modality": "text",
          "value": "It would reward the quickest students at the expense of the rest",
          "short": "It rewards the quickest at others' expense"
        }
      ],
      "correctIndex": 0,
      "explanation": "The design choice is pedagogical: a system that supplies answers on demand undermines the productive struggle that makes learning stick — knowledge a learner constructs through guided questioning encodes more durably than knowledge merely received.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1gtsiwt1j1o9dr"
    },
    {
      "id": "ot-khanmigo-5",
      "shape": "mcq",
      "tags": [
        "khanmigo",
        "socratic",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "A student asks Khanmigo for the solution to an equation. Consistent with its design, it should do what?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Let the student pick either a hint or the full worked solution"
        },
        {
          "modality": "text",
          "value": "Swap in an easier equation the student can solve on their own"
        },
        {
          "modality": "text",
          "value": "Ask a question that moves the student toward the next step"
        },
        {
          "modality": "text",
          "value": "Walk the student through the full solution one step at a time"
        }
      ],
      "correctIndex": 2,
      "explanation": "Khanmigo is built to refuse direct answers and respond with guiding questions, because handing over the answer would undermine the productive struggle that makes learning stick.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "ygybl16r0woj"
    },
    {
      "id": "ot-stakes-1",
      "shape": "mcq",
      "tags": [
        "beyond-k12",
        "stakes"
      ],
      "prompt": {
        "modality": "text",
        "value": "Beyond K-12, Brave New Words extends the case for AI-assisted learning to which three domains?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Graduate study, professional licensing, and local government"
        },
        {
          "modality": "text",
          "value": "Adult literacy, immigrant integration, and jury service"
        },
        {
          "modality": "text",
          "value": "College admissions, the workplace, and civic participation"
        },
        {
          "modality": "text",
          "value": "Trade apprenticeships, the gig economy, and public health"
        }
      ],
      "correctIndex": 2,
      "explanation": "Khan names college admissions, the workplace, and civic participation — treating AI tutoring as lifelong infrastructure rather than a school feature.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "15sgogf1hv7499"
    },
    {
      "id": "ot-stakes-2",
      "shape": "mcq",
      "tags": [
        "infrastructure",
        "stakes"
      ],
      "prompt": {
        "modality": "text",
        "value": "Khan frames AI tutoring as \"infrastructure.\" What does that framing claim?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It is a lifelong utility, like electricity or the internet — not a school feature",
          "short": "A lifelong utility, like electricity"
        },
        {
          "modality": "text",
          "value": "It is a base that other tools build on, like a power grid — not an end product",
          "short": "A base other tools build on"
        },
        {
          "modality": "text",
          "value": "It is a collective investment, like highways or dams — not a private venture",
          "short": "A collective investment, like highways"
        },
        {
          "modality": "text",
          "value": "It is an invisible background layer, like plumbing or wiring — not a visible tool",
          "short": "An invisible layer, like plumbing"
        }
      ],
      "correctIndex": 0,
      "explanation": "The infrastructure framing is about scope: AI tutoring is a lifelong utility the way electricity and the internet are not just for students.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "7za3zvytvnmx"
    },
    {
      "id": "ot-stakes-4",
      "shape": "mcq",
      "tags": [
        "warner",
        "ethics",
        "reception"
      ],
      "prompt": {
        "modality": "text",
        "value": "Khan answers the risks he names with a case for responsible deployment. Which three practices does the guide say that case rests on?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Informed consent, algorithmic fairness, and open access",
          "short": "Consent, fairness, open access"
        },
        {
          "modality": "text",
          "value": "Teacher autonomy, gradual rollout, and open-source models",
          "short": "Autonomy, gradual rollout, open source"
        },
        {
          "modality": "text",
          "value": "Data minimization, content filtering, and equity audits",
          "short": "Data minimization, filtering, audits"
        },
        {
          "modality": "text",
          "value": "Transparency, human oversight, and ongoing evaluation",
          "short": "Transparency, oversight, evaluation"
        }
      ],
      "correctIndex": 3,
      "explanation": "Khan's responsible-deployment argument rests on transparency, human oversight, and ongoing evaluation — adopting imperfect tools carefully rather than waiting for hallucination, bias and privacy risks to disappear.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "wr082scx3ois"
    },
    {
      "id": "ot-stakes-5",
      "shape": "mcq",
      "tags": [
        "warner",
        "evidence",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "Warner's central charge is that Khan trades on technology optimism. Which evidence would most directly answer that charge?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Controlled research showing students using the AI tutor learn more",
          "short": "Controlled study of learning gains"
        },
        {
          "modality": "text",
          "value": "Peer-reviewed benchmarks showing the underlying model aces hard exams",
          "short": "Benchmarks showing the model aces exams"
        },
        {
          "modality": "text",
          "value": "An independent survey finding students rate the tutor as helpful",
          "short": "Survey: students rate tutor helpful"
        },
        {
          "modality": "text",
          "value": "Longitudinal usage data showing students return to the tutor daily",
          "short": "Usage data: students return daily"
        }
      ],
      "correctIndex": 0,
      "explanation": "Warner's objection is that Khan expects transformation because the tools are impressive, not because controlled research shows learning gains.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1rbbybr45s0rp"
    },
    {
      "id": "ot-taxonomy-1",
      "shape": "mcq",
      "tags": [
        "taxonomy",
        "teacher-tools"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which function defines the Teacher Tools category, whose leading players include MagicSchool and Diffit?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Adaptive dialogue, one-to-one tutoring, and pace adjustment"
        },
        {
          "modality": "text",
          "value": "Progress tracking, formative assessment, and class analytics"
        },
        {
          "modality": "text",
          "value": "Document synthesis, source grounding, and knowledge retrieval"
        },
        {
          "modality": "text",
          "value": "Lesson planning, rubric generation, and admin reduction"
        }
      ],
      "correctIndex": 3,
      "explanation": "Teacher Tools keep the human educator central by handling lesson planning, rubrics, and administrative load. Adaptive one-to-one tutoring is the AI Tutors category, progress tracking is Assessment & Analytics, and source-grounded document synthesis is Research Assistants.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "17k45kpd2s4vf"
    },
    {
      "id": "ot-taxonomy-2",
      "shape": "mcq",
      "tags": [
        "taxonomy",
        "enterprise"
      ],
      "prompt": {
        "modality": "text",
        "value": "Sana, Coursera, Udemy, and Multiverse are the named players in which category?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Assessment & Analytics"
        },
        {
          "modality": "text",
          "value": "Enterprise / Workforce"
        },
        {
          "modality": "text",
          "value": "Research Assistants"
        },
        {
          "modality": "text",
          "value": "Micro / Game Learning"
        }
      ],
      "correctIndex": 1,
      "explanation": "Enterprise / Workforce platforms focus on upskilling and corporate training where measurable job-readiness matters to the buyer. Assessment & Analytics is Gradescope, Eedi, and MagicQuizzes.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "by9yu8gf8src"
    },
    {
      "id": "ot-taxonomy-5",
      "shape": "mcq",
      "tags": [
        "taxonomy",
        "ai-tutors"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which three products does the guide place in the AI Tutors category — adaptive, conversational 1:1 instruction?"
      },
      "options": [
        {
          "modality": "text",
          "value": "MagicSchool, Diffit, and Perplexity"
        },
        {
          "modality": "text",
          "value": "Duolingo, Lingokids, and Kahoot"
        },
        {
          "modality": "text",
          "value": "Khanmigo, Synthesis, and LearnLM"
        },
        {
          "modality": "text",
          "value": "Gradescope, Eedi, and MagicQuizzes"
        }
      ],
      "correctIndex": 2,
      "explanation": "The guide's AI Tutors are Khanmigo, Synthesis, and LearnLM: adaptive, conversational 1:1 instruction, the closest digital analog to a personal teacher.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1jez4qec7eayi"
    },
    {
      "id": "ot-taxonomy-3",
      "shape": "mcq",
      "tags": [
        "taxonomy",
        "assessment"
      ],
      "prompt": {
        "modality": "text",
        "value": "What function does the guide assign to the Assessment & Analytics category (Gradescope, Eedi, MagicQuizzes)?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Adaptive vocabulary sequencing that replaces rote grammar drills",
          "short": "Vocab sequencing replacing drills"
        },
        {
          "modality": "text",
          "value": "Document synthesis that grounds answers in the provided sources",
          "short": "Source-grounded document synthesis"
        },
        {
          "modality": "text",
          "value": "Progress tracking that surfaces where a class is collectively lost",
          "short": "Tracking where a class is lost"
        },
        {
          "modality": "text",
          "value": "Game-based challenges that consolidate lessons after instruction",
          "short": "Game challenges that consolidate"
        }
      ],
      "correctIndex": 2,
      "explanation": "Assessment & Analytics tools handle progress tracking and formative assessment, surfacing where a class is collectively lost. Adaptive vocabulary sequencing is Language Learning, source-grounded synthesis is Research Assistants, and game-based challenges are Micro / Game.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "11tul5eve7b2"
    },
    {
      "id": "ot-taxonomy-4",
      "shape": "mcq",
      "tags": [
        "taxonomy",
        "game-learning"
      ],
      "prompt": {
        "modality": "text",
        "value": "A school adopts Kahoot and Blooket for quick, competitive review rounds after direct instruction. Which category is that, and what role does it serve?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Teacher Tools — a lesson-planning and admin-reduction layer"
        },
        {
          "modality": "text",
          "value": "AI Tutors — a primary instruction and adaptive dialogue layer"
        },
        {
          "modality": "text",
          "value": "Micro / Game Learning — a consolidation and motivation layer"
        },
        {
          "modality": "text",
          "value": "Enterprise / Workforce — a job-readiness and upskilling layer"
        }
      ],
      "correctIndex": 2,
      "explanation": "Kahoot, Blooket, and Synthesis Teams are Micro / Game Learning: game-based, challenge-driven engagement used primarily as a consolidation or motivation layer, not as primary instruction.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "hghnua488pjq"
    },
    {
      "id": "ot-platforms-1",
      "shape": "mcq",
      "tags": [
        "khanmigo",
        "scale"
      ],
      "prompt": {
        "modality": "text",
        "value": "How many K-12 students was Khanmigo serving by the 2024–25 academic year?"
      },
      "options": [
        {
          "modality": "text",
          "value": "700,000"
        },
        {
          "modality": "text",
          "value": "1,500,000"
        },
        {
          "modality": "text",
          "value": "250,000"
        },
        {
          "modality": "text",
          "value": "2,000,000"
        }
      ],
      "correctIndex": 0,
      "explanation": "Khanmigo served 700,000 K-12 students by 2024–25. The 2+ million figure belongs to MagicSchool AI — but that counts educators, not students.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "uuiilx195kj6n"
    },
    {
      "id": "ot-platforms-2",
      "shape": "mcq",
      "tags": [
        "duolingo",
        "birdbrain"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which of these does the guide assign to Duolingo's proprietary BirdBrain model rather than to the GPT-4-powered Max tier?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Running open conversation practice through a chat character",
          "short": "Open-conversation chat practice"
        },
        {
          "modality": "text",
          "value": "Sequencing and personalizing lessons from performance history",
          "short": "Sequencing lessons by performance"
        },
        {
          "modality": "text",
          "value": "Staging roleplay scenarios for situational language practice",
          "short": "Roleplay scenarios for practice"
        },
        {
          "modality": "text",
          "value": "Explaining why a learner's submitted answer was right or wrong",
          "short": "Explaining why an answer was wrong"
        }
      ],
      "correctIndex": 1,
      "explanation": "BirdBrain is the proprietary adaptive engine that sequences and personalizes lessons from each learner's performance history. Roleplay scenarios, 'Explain My Answer', and the Lily open-conversation chat mode are GPT-4-powered Max-tier features layered on top of it.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "17ihreb4brrc1"
    },
    {
      "id": "ot-platforms-3",
      "shape": "mcq",
      "tags": [
        "adaptive-learning",
        "definition"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which definition matches an adaptive learning system?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Software that drafts lesson plans, rubrics, and quizzes to cut a teacher's administrative load",
          "short": "Drafts plans, rubrics, quizzes"
        },
        {
          "modality": "text",
          "value": "Software that scores work, tracks progress, and shows where a class is collectively lost",
          "short": "Scores work, shows class gaps"
        },
        {
          "modality": "text",
          "value": "Software that grounds every answer in user-supplied documents and returns summaries or audio",
          "short": "Grounds answers in source documents"
        },
        {
          "modality": "text",
          "value": "Software that adjusts content, sequence, and difficulty in real time from performance history",
          "short": "Adjusts difficulty in real time"
        }
      ],
      "correctIndex": 3,
      "explanation": "An adaptive learning system adjusts content, sequence, and difficulty in real time based on each learner's performance history — Duolingo's BirdBrain is the example. Source-grounded responses describe NotebookLM instead.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "j0lofg181ikyk"
    },
    {
      "id": "ot-evidence-1",
      "shape": "mcq",
      "tags": [
        "learnlm",
        "rct"
      ],
      "prompt": {
        "modality": "text",
        "value": "In the 2025 Google/Eedi Labs RCT, what success rate did LearnLM students reach on subsequent harder topics?"
      },
      "options": [
        {
          "modality": "text",
          "value": "61%"
        },
        {
          "modality": "text",
          "value": "76%"
        },
        {
          "modality": "text",
          "value": "56%"
        },
        {
          "modality": "text",
          "value": "66%"
        }
      ],
      "correctIndex": 3,
      "explanation": "LearnLM students hit 66%, ahead of the human-tutor group's 61% and static hints' 56%. The 76% option rounds the 76.4% share of LearnLM responses human tutors approved with little or no edits — a quality signal, not the outcome.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "yug0gt799gun"
    },
    {
      "id": "ot-evidence-3",
      "shape": "mcq",
      "tags": [
        "learnlm",
        "rct"
      ],
      "prompt": {
        "modality": "text",
        "value": "In the LearnLM RCT, what did the 76.4% figure measure?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Questions LearnLM answered without a factual error",
          "short": "Questions answered without error"
        },
        {
          "modality": "text",
          "value": "LearnLM responses human tutors approved with little or no edits",
          "short": "Responses tutors approved unedited"
        },
        {
          "modality": "text",
          "value": "Students who preferred the AI tutor to a human tutor",
          "short": "Students preferring AI to human tutor"
        },
        {
          "modality": "text",
          "value": "Students who completed the full trial",
          "short": "Students who finished the trial"
        }
      ],
      "correctIndex": 1,
      "explanation": "Human tutors reviewing LearnLM's responses approved 76.4% with little or no edits — a quality signal, not an outcome or preference measure. The outcome measure was the 66% success rate.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "jlon22ozatem"
    },
    {
      "id": "ot-evidence-4",
      "shape": "mcq",
      "tags": [
        "its",
        "definition"
      ],
      "prompt": {
        "modality": "text",
        "value": "What distinguishes an intelligent tutoring system from a simple hint-delivery tool?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It models the subject and infers each learner's level from the class average",
          "short": "Subject model plus class average"
        },
        {
          "modality": "text",
          "value": "It times each learner's responses and reorders a shared hint sequence to match",
          "short": "Times responses, reorders hints"
        },
        {
          "modality": "text",
          "value": "It routes each learner's question to a human tutor and stores the reply",
          "short": "Relays questions to a human tutor"
        },
        {
          "modality": "text",
          "value": "It models both the subject and the learner's evolving understanding",
          "short": "Models both subject and learner"
        }
      ],
      "correctIndex": 3,
      "explanation": "An intelligent tutoring system models both the subject and the learner's evolving understanding to deliver individualized feedback — that dual model is what a static-hints tool lacks.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "jropys1dj4vz8"
    },
    {
      "id": "ot-evidence-2",
      "shape": "mcq",
      "tags": [
        "rct",
        "comparison"
      ],
      "prompt": {
        "modality": "text",
        "value": "Rank the three LearnLM RCT conditions from highest to lowest success rate on harder follow-up topics."
      },
      "options": [
        {
          "modality": "text",
          "value": "AI tutor, human tutor, static hints"
        },
        {
          "modality": "text",
          "value": "Human tutor, static hints, AI tutor"
        },
        {
          "modality": "text",
          "value": "AI tutor, static hints, human tutor"
        },
        {
          "modality": "text",
          "value": "Human tutor, AI tutor, static hints"
        }
      ],
      "correctIndex": 0,
      "explanation": "The AI tutor (LearnLM) led at 66%, the human-tutor group followed at 61%, and static hints trailed at 56% — a 10-point spread between best and worst.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1e3p7rq12f0x2a"
    },
    {
      "id": "ot-market-1",
      "shape": "mcq",
      "tags": [
        "market-size",
        "adaptive-learning"
      ],
      "prompt": {
        "modality": "text",
        "value": "What was the adaptive learning platform market valued at in 2025, and what is it projected to reach by 2032?"
      },
      "options": [
        {
          "modality": "text",
          "value": "$2.6 billion → $5.47 billion"
        },
        {
          "modality": "text",
          "value": "$1.72 billion → $10.7 billion"
        },
        {
          "modality": "text",
          "value": "$2.6 billion → $10.7 billion"
        },
        {
          "modality": "text",
          "value": "$1.72 billion → $5.47 billion"
        }
      ],
      "correctIndex": 3,
      "explanation": "The adaptive learning platform market was $1.72B in 2025, projected to $5.47B by 2032 — roughly 3x over seven years. The $2.6B figure is total 2025 global EdTech investment, a different measure.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "gve8821qn353y"
    },
    {
      "id": "ot-market-2",
      "shape": "mcq",
      "tags": [
        "investment",
        "market"
      ],
      "prompt": {
        "modality": "text",
        "value": "Global EdTech investment in 2025 hit $2.6 billion. Roughly how much was that up over 2024?"
      },
      "options": [
        {
          "modality": "text",
          "value": "About 11%"
        },
        {
          "modality": "text",
          "value": "About 38%"
        },
        {
          "modality": "text",
          "value": "About 22%"
        },
        {
          "modality": "text",
          "value": "About 4%"
        }
      ],
      "correctIndex": 0,
      "explanation": "2025 global EdTech investment reached $2.6B, up roughly 11% over 2024, with capital concentrating in AI-enabled and workforce-aligned products. The 38%, 22%, and 4% figures are 2025 deal-volume shares (workforce, post-secondary, early childhood), not growth rates.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "sd9phu13bh53a"
    },
    {
      "id": "ot-market-3",
      "shape": "mcq",
      "tags": [
        "deals",
        "acquisitions"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which pairing of 2025's two headline deals with their values is correct?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Workday–Sana $1.1B; Coursera–Udemy $2.5B"
        },
        {
          "modality": "text",
          "value": "Workday–Sana $2.5B; Coursera–Udemy $1.1B"
        },
        {
          "modality": "text",
          "value": "Workday–Sana $1.72B; Coursera–Udemy $2.6B"
        },
        {
          "modality": "text",
          "value": "Workday–Sana $2.6B; Coursera–Udemy $1.72B"
        }
      ],
      "correctIndex": 0,
      "explanation": "Workday acquired Sana for $1.1B, and Coursera's all-stock acquisition of Udemy was $2.5B (Dec 2025). The $1.72B and $2.6B figures are the 2025 adaptive-learning market size and total EdTech investment, not deal values.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "uc1wlmutgeum"
    },
    {
      "id": "ot-market-4",
      "shape": "mcq",
      "tags": [
        "deals",
        "coursera"
      ],
      "prompt": {
        "modality": "text",
        "value": "The Coursera–Udemy acquisition created a combined platform of what scale?"
      },
      "options": [
        {
          "modality": "text",
          "value": "180 million learners and 28,000 enterprise customers"
        },
        {
          "modality": "text",
          "value": "290 million learners and 28,000 enterprise customers"
        },
        {
          "modality": "text",
          "value": "290 million learners and 18,000 enterprise customers"
        },
        {
          "modality": "text",
          "value": "180 million learners and 18,000 enterprise customers"
        }
      ],
      "correctIndex": 2,
      "explanation": "The $2.5B all-stock Coursera–Udemy deal combined into 290 million learners and 18,000 enterprise customers. The other pairings swap in figures the guide never gives for either number.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "qpf66f19oan2l"
    },
    {
      "id": "ot-platcat-1",
      "shape": "mcq",
      "tags": [
        "categories",
        "ai-tutors"
      ],
      "prompt": {
        "modality": "text",
        "value": "The guide lists Synthesis under AI Tutors. Under which category does it list Synthesis Teams?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Assessment & Analytics"
        },
        {
          "modality": "text",
          "value": "Micro / Game Learning"
        },
        {
          "modality": "text",
          "value": "Enterprise / Workforce"
        },
        {
          "modality": "text",
          "value": "Research Assistants"
        }
      ],
      "correctIndex": 1,
      "explanation": "Synthesis itself is the K-6 adaptive math tutor and sits under AI Tutors with Khanmigo and LearnLM; Synthesis Teams appears under Micro / Game Learning alongside Kahoot and Blooket, as a game-based consolidation and motivation layer rather than primary instruction.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "8viqhk12j1xq0"
    },
    {
      "id": "ot-platcat-2",
      "shape": "mcq",
      "tags": [
        "categories",
        "magicschool"
      ],
      "prompt": {
        "modality": "text",
        "value": "MagicSchool AI sits in the same category as which other named platform?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Kahoot"
        },
        {
          "modality": "text",
          "value": "Diffit"
        },
        {
          "modality": "text",
          "value": "Eedi"
        },
        {
          "modality": "text",
          "value": "Sana"
        }
      ],
      "correctIndex": 1,
      "explanation": "MagicSchool and Diffit are both Teacher Tools — lesson planning, rubric generation, admin reduction. Kahoot is Micro / Game Learning, Eedi is Assessment & Analytics, and Sana is Enterprise / Workforce.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "5gua9s1ouv9gw"
    },
    {
      "id": "ot-platcat-4",
      "shape": "mcq",
      "tags": [
        "categories",
        "duolingo"
      ],
      "prompt": {
        "modality": "text",
        "value": "A parent wants an app that adapts vocabulary from their child's performance history and replaces rote grammar drills with conversation practice. Which platform fits?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Sana — Enterprise / Workforce"
        },
        {
          "modality": "text",
          "value": "Blooket — Micro / Game Learning"
        },
        {
          "modality": "text",
          "value": "Gradescope — Assessment & Analytics"
        },
        {
          "modality": "text",
          "value": "Duolingo — Language Learning"
        }
      ],
      "correctIndex": 3,
      "explanation": "Duolingo is the flagship of Language Learning (with Lingokids), where adaptive vocabulary sequencing and conversation practice replace rote drills. The other three platforms are correctly paired but serve different functions.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "r43yl6wmrigu"
    },
    {
      "id": "ot-platcat-3",
      "shape": "mcq",
      "tags": [
        "categories",
        "duolingo"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which platform-to-category pairing follows the guide's taxonomy?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Perplexity — Research Assistants"
        },
        {
          "modality": "text",
          "value": "Duolingo — Micro / Game Learning"
        },
        {
          "modality": "text",
          "value": "Gradescope — Teacher Tools"
        },
        {
          "modality": "text",
          "value": "Kahoot — Assessment & Analytics"
        }
      ],
      "correctIndex": 0,
      "explanation": "The guide files Perplexity with NotebookLM under Research Assistants — document synthesis and multi-source retrieval. Duolingo and Lingokids anchor Language Learning, not game learning or AI tutoring, and Gradescope sits in Assessment & Analytics rather than Teacher Tools.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1hyu1yl185q85j"
    },
    {
      "id": "ot-lms-history-1",
      "shape": "mcq",
      "tags": [
        "pressey",
        "lms-history",
        "dates"
      ],
      "prompt": {
        "modality": "text",
        "value": "In what year did Sidney Pressey build his mechanical teaching machine?"
      },
      "options": [
        {
          "modality": "text",
          "value": "1924"
        },
        {
          "modality": "text",
          "value": "1938"
        },
        {
          "modality": "text",
          "value": "1954"
        },
        {
          "modality": "text",
          "value": "1912"
        }
      ],
      "correctIndex": 0,
      "explanation": "Pressey's typewriter-sized machine appeared in 1924, presenting multiple-choice questions and advancing only on a correct answer. The other years bracket it but are not the milestone.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "10gxa3k1u0pw40"
    },
    {
      "id": "ot-lms-history-2",
      "shape": "mcq",
      "tags": [
        "plato",
        "bitzer",
        "dates"
      ],
      "prompt": {
        "modality": "text",
        "value": "Donald Bitzer launched PLATO at the University of Illinois in which year?"
      },
      "options": [
        {
          "modality": "text",
          "value": "1970"
        },
        {
          "modality": "text",
          "value": "1950"
        },
        {
          "modality": "text",
          "value": "1960"
        },
        {
          "modality": "text",
          "value": "1980"
        }
      ],
      "correctIndex": 2,
      "explanation": "PLATO (Programmed Logic for Automated Teaching Operations) launched in 1960 — a mainframe system with simultaneous users and touchscreens, anticipating modern e-learning by thirty years.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1asfs2tsifcqn"
    },
    {
      "id": "ot-lms-history-3",
      "shape": "mcq",
      "tags": [
        "moodle",
        "dougiamas",
        "dates"
      ],
      "prompt": {
        "modality": "text",
        "value": "In what year did Martin Dougiamas release Moodle as open-source software?"
      },
      "options": [
        {
          "modality": "text",
          "value": "2011"
        },
        {
          "modality": "text",
          "value": "2006"
        },
        {
          "modality": "text",
          "value": "2002"
        },
        {
          "modality": "text",
          "value": "1998"
        }
      ],
      "correctIndex": 2,
      "explanation": "Moodle arrived in 2002, a year after SCORM, shifting power toward institutions unwilling to pay enterprise licensing fees. 1998 predates the open-source release; 2006 and 2011 fall too late, into the web and cloud LMS eras.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "qzmag7y3qgf1"
    },
    {
      "id": "ot-lms-history-4",
      "shape": "mcq",
      "tags": [
        "sequence",
        "lms-history"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which sequence puts the LMS milestones in correct chronological order?"
      },
      "options": [
        {
          "modality": "text",
          "value": "PLATO → Pressey's machine → SCORM → Moodle"
        },
        {
          "modality": "text",
          "value": "Pressey's machine → PLATO → Moodle → SCORM"
        },
        {
          "modality": "text",
          "value": "Pressey's machine → PLATO → SCORM → Moodle"
        },
        {
          "modality": "text",
          "value": "PLATO → Pressey's machine → Moodle → SCORM"
        }
      ],
      "correctIndex": 2,
      "explanation": "The order is 1924 (Pressey), 1960 (PLATO), 2001 (SCORM), 2002 (Moodle). Pressey's mechanical machine came 36 years before Bitzer's mainframe, and SCORM arrived the year before Moodle, not the year after.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1uukjqbb232w1"
    },
    {
      "id": "ot-lms-history-5",
      "shape": "mcq",
      "tags": [
        "dates",
        "pressey",
        "plato"
      ],
      "prompt": {
        "modality": "text",
        "value": "Roughly how many years separate Pressey's teaching machine from the launch of PLATO?"
      },
      "options": [
        {
          "modality": "text",
          "value": "48 years"
        },
        {
          "modality": "text",
          "value": "36 years"
        },
        {
          "modality": "text",
          "value": "22 years"
        },
        {
          "modality": "text",
          "value": "61 years"
        }
      ],
      "correctIndex": 1,
      "explanation": "1960 minus 1924 is 36 years, mechanical era to mainframe era. The other gaps each swap a wrong year in for one milestone — 22 years counts from 1938, 48 from 1912 (or to 1972), 61 to 1985.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "jt48x31502i19"
    },
    {
      "id": "ot-lms-platforms-1",
      "shape": "mcq",
      "tags": [
        "moodle",
        "open-source",
        "platforms"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which LMS was released as open-source software and became dominant in international higher education?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Blackboard"
        },
        {
          "modality": "text",
          "value": "Moodle"
        },
        {
          "modality": "text",
          "value": "PLATO"
        },
        {
          "modality": "text",
          "value": "Canvas"
        }
      ],
      "correctIndex": 1,
      "explanation": "Moodle's constructivist design and zero cost made it the global open-source leader. Canvas and Blackboard are commercial; PLATO was a 1960 mainframe system.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "4f2ie8bfza20"
    },
    {
      "id": "ot-lms-platforms-2",
      "shape": "mcq",
      "tags": [
        "blackboard",
        "platforms"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which platform's reputation for clunky UX and aggressive pricing created openings for nimbler competitors?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Blackboard"
        },
        {
          "modality": "text",
          "value": "PLATO"
        },
        {
          "modality": "text",
          "value": "Moodle"
        },
        {
          "modality": "text",
          "value": "Canvas"
        }
      ],
      "correctIndex": 0,
      "explanation": "Blackboard was the long-entrenched incumbent whose clunky UX and pricing let Canvas take share. Moodle competed on cost, and Canvas is the one praised for a clean interface.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "y1cmhx3pqihb"
    },
    {
      "id": "ot-lms-platforms-3",
      "shape": "mcq",
      "tags": [
        "canvas",
        "instructure",
        "platforms"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which company makes Canvas?"
      },
      "options": [
        {
          "modality": "text",
          "value": "PowerSchool"
        },
        {
          "modality": "text",
          "value": "McGraw Hill"
        },
        {
          "modality": "text",
          "value": "Instructure"
        },
        {
          "modality": "text",
          "value": "Blackboard"
        }
      ],
      "correctIndex": 2,
      "explanation": "Canvas is built by Instructure. Blackboard Inc. sells the rival product Canvas took share from, while PowerSchool and Pearson are other education-technology vendors with no hand in Canvas.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "srunhb8ndd0l"
    },
    {
      "id": "ot-lms-platforms-4",
      "shape": "mcq",
      "tags": [
        "plato",
        "platforms",
        "eras"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which delivery-technology era does the guide assign to PLATO?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The public-web era"
        },
        {
          "modality": "text",
          "value": "The cloud/SaaS era"
        },
        {
          "modality": "text",
          "value": "The mainframe era"
        },
        {
          "modality": "text",
          "value": "The mechanical era"
        }
      ],
      "correctIndex": 2,
      "explanation": "PLATO was Bitzer's 1960 mainframe-based system at the University of Illinois, with simultaneous users and touchscreens. Pressey's 1924 machine belongs to the mechanical era; Moodle arrived with the web, and Canvas and Blackboard fought it out in the cloud/SaaS era.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "pgc5617x9fk3"
    },
    {
      "id": "ot-interop-1",
      "shape": "mcq",
      "tags": [
        "scorm",
        "standards"
      ],
      "prompt": {
        "modality": "text",
        "value": "What does SCORM stand for?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Sharable Content Object Runtime Manifest"
        },
        {
          "modality": "text",
          "value": "Sharable Content Organization Reference Manifest"
        },
        {
          "modality": "text",
          "value": "Sharable Content Organization Runtime Model"
        },
        {
          "modality": "text",
          "value": "Sharable Content Object Reference Model"
        }
      ],
      "correctIndex": 3,
      "explanation": "SCORM is the Sharable Content Object Reference Model, introduced in 2001 to give vendors a common language for packaging and tracking content across LMSs. The other expansions keep the initials but swap in look-alike words; none is the standard's name.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "h2ua011p79rgr"
    },
    {
      "id": "ot-interop-2",
      "shape": "mcq",
      "tags": [
        "scorm",
        "tracking"
      ],
      "prompt": {
        "modality": "text",
        "value": "What kind of learning data does SCORM track?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Forum posts and peer feedback only"
        },
        {
          "modality": "text",
          "value": "Simulation events and mobile logs only"
        },
        {
          "modality": "text",
          "value": "Completions and quiz scores only"
        },
        {
          "modality": "text",
          "value": "Offline and on-the-job experiences only"
        }
      ],
      "correctIndex": 2,
      "explanation": "SCORM is limited to completions and quiz scores reported by content inside the LMS. Simulation, mobile, offline and on-the-job activity is what the later xAPI (Tin Can) era captures via Actor-Verb-Object statements, and forum posts are LMS features outside SCORM's content-tracking remit.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "12h0xdhofw6an"
    },
    {
      "id": "ot-interop-3",
      "shape": "mcq",
      "tags": [
        "lrs",
        "xapi",
        "standards"
      ],
      "prompt": {
        "modality": "text",
        "value": "What is the Learning Record Store (LRS)?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The packaging standard that moves content between LMSs"
        },
        {
          "modality": "text",
          "value": "The LMS module that records completions and quiz scores"
        },
        {
          "modality": "text",
          "value": "The backend database that stores xAPI statements"
        },
        {
          "modality": "text",
          "value": "The Actor-Verb-Object format used to log learning activity"
        }
      ],
      "correctIndex": 2,
      "explanation": "The LRS is a portable, durable backend repository of xAPI statements across systems. It stores records — it is not the SCORM packaging standard, not the LMS-side tally of completions and quiz scores, and not the Actor-Verb-Object statement format itself.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "khuij8pfxx0"
    },
    {
      "id": "ot-interop-4",
      "shape": "mcq",
      "tags": [
        "xapi",
        "standards",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "A firefighter completes a live drill with no LMS involved and the activity is logged. Which standard makes this possible?"
      },
      "options": [
        {
          "modality": "text",
          "value": "SCORM 1.2"
        },
        {
          "modality": "text",
          "value": "xAPI (Tin Can)"
        },
        {
          "modality": "text",
          "value": "The Learning Record Store"
        },
        {
          "modality": "text",
          "value": "SCORM 2004"
        }
      ],
      "correctIndex": 1,
      "explanation": "xAPI extends tracking beyond the LMS boundary to simulations, mobile apps, and the physical world. SCORM only tracks completions and scores inside an LMS; the LRS stores the statements but is not itself a standard.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "z161z813r0q2k"
    },
    {
      "id": "ot-gamification-1",
      "shape": "mcq",
      "tags": [
        "gamification",
        "pelling",
        "definition"
      ],
      "prompt": {
        "modality": "text",
        "value": "Who coined the term \"gamification,\" and in what year?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Thomas Malone, 1980"
        },
        {
          "modality": "text",
          "value": "Karl Kapp, 2012"
        },
        {
          "modality": "text",
          "value": "Jane McGonigal, 2011"
        },
        {
          "modality": "text",
          "value": "Nick Pelling, 2003"
        }
      ],
      "correctIndex": 3,
      "explanation": "Nick Pelling coined gamification in 2003. Malone's 1980 research predates the term; McGonigal and Kapp wrote later books but did not name the concept.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "6y83nr1g695zx"
    },
    {
      "id": "ot-gamification-2",
      "shape": "mcq",
      "tags": [
        "gamification",
        "definition"
      ],
      "prompt": {
        "modality": "text",
        "value": "Gamification is best defined as which of the following?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Identifying which features make computer games intrinsically engaging",
          "short": "Identifying what makes games engaging"
        },
        {
          "modality": "text",
          "value": "Applying game design elements to non-game contexts to boost engagement",
          "short": "Game elements in non-game contexts"
        },
        {
          "modality": "text",
          "value": "Designing systems in which players engage in artificial conflict defined by rules",
          "short": "Designing rule-bound artificial conflict"
        },
        {
          "modality": "text",
          "value": "Building full-fledged video games to deliver instruction in classrooms",
          "short": "Building full video games for class"
        }
      ],
      "correctIndex": 1,
      "explanation": "Gamification applies game elements — points, badges, leaderboards, levels, narrative — to non-game contexts. What makes games engaging was Malone's 1980 question, building actual games is a different practice, and rule-defined conflict is Salen & Zimmerman's definition of games.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1hh7roo7ma28"
    },
    {
      "id": "ot-gamification-3",
      "shape": "mcq",
      "tags": [
        "mcgonigal",
        "thinkers"
      ],
      "prompt": {
        "modality": "text",
        "value": "Match the thinker to the work: who wrote Reality Is Broken (2011)?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Nick Pelling"
        },
        {
          "modality": "text",
          "value": "Karl Kapp"
        },
        {
          "modality": "text",
          "value": "Jesse Schell"
        },
        {
          "modality": "text",
          "value": "Jane McGonigal"
        }
      ],
      "correctIndex": 3,
      "explanation": "McGonigal's Reality Is Broken argued games motivate better than real-world institutions. Kapp wrote The Gamification of Learning and Instruction (2012); Schell gave the 2010 DICE talk.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "8hzvyw1pnmt14"
    },
    {
      "id": "ot-gamification-4",
      "shape": "mcq",
      "tags": [
        "thinkers",
        "malone",
        "salen-zimmerman"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which pairing of thinker and contribution is INCORRECT?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Thomas Malone — Rules of Play (2004)",
          "short": "Thomas Malone — Rules of Play (2004)"
        },
        {
          "modality": "text",
          "value": "Jane McGonigal — Reality Is Broken (2011)",
          "short": "Jane McGonigal — Reality Is Broken (2011)"
        },
        {
          "modality": "text",
          "value": "Jesse Schell — DICE conference talk (2010)",
          "short": "Jesse Schell — DICE conference talk (2010)"
        },
        {
          "modality": "text",
          "value": "Deci & Ryan — Self-Determination Theory (1985)",
          "short": "Deci & Ryan — Self-Determination (1985)"
        }
      ],
      "correctIndex": 0,
      "explanation": "Rules of Play (2004) is Salen & Zimmerman's. Malone's 1980 research identified challenge, fantasy, and curiosity as what makes games engaging. McGonigal, Schell, and Deci & Ryan are each paired correctly.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "x4ngzn1sy4l7l"
    },
    {
      "id": "ot-sdt-1",
      "shape": "mcq",
      "tags": [
        "sdt",
        "deci-ryan"
      ],
      "prompt": {
        "modality": "text",
        "value": "Who developed Self-Determination Theory, and in what year?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Salen & Zimmerman, 2004"
        },
        {
          "modality": "text",
          "value": "Deci & Ryan, 1985"
        },
        {
          "modality": "text",
          "value": "Pelling, 2003"
        },
        {
          "modality": "text",
          "value": "Malone, 1980"
        }
      ],
      "correctIndex": 1,
      "explanation": "Edward Deci and Richard Ryan developed SDT in 1985. Malone researched game motivation, Pelling coined gamification, and Salen & Zimmerman wrote the game-design rules text.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1345to814s5l9c"
    },
    {
      "id": "ot-sdt-2",
      "shape": "mcq",
      "tags": [
        "sdt",
        "needs"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which trio names SDT's three basic psychological needs?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Autonomy, competence, relatedness"
        },
        {
          "modality": "text",
          "value": "Challenge, fantasy, curiosity"
        },
        {
          "modality": "text",
          "value": "Points, badges, leaderboards"
        },
        {
          "modality": "text",
          "value": "Attention, relevance, satisfaction"
        }
      ],
      "correctIndex": 0,
      "explanation": "SDT names autonomy, competence, and relatedness. Challenge, fantasy, and curiosity are Malone's game-motivation drivers; points and badges are surface mechanics, not needs.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "h3tuyx1chmmb"
    },
    {
      "id": "ot-sdt-3",
      "shape": "mcq",
      "tags": [
        "sdt",
        "autonomy",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "Letting a learner choose their own path through a course primarily satisfies which SDT need?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Competence"
        },
        {
          "modality": "text",
          "value": "Autonomy"
        },
        {
          "modality": "text",
          "value": "Curiosity"
        },
        {
          "modality": "text",
          "value": "Relatedness"
        }
      ],
      "correctIndex": 1,
      "explanation": "Autonomy is feeling in control of one's actions, which choice of path directly serves. Competence comes from progressive difficulty; relatedness from cooperative or competitive play. Curiosity is one of Malone's game-motivation drivers, not an SDT need.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1pmlmu3tktmyx"
    },
    {
      "id": "ot-sdt-4",
      "shape": "mcq",
      "tags": [
        "autotelic",
        "flow",
        "intrinsic"
      ],
      "prompt": {
        "modality": "text",
        "value": "What is an autotelic activity?"
      },
      "options": [
        {
          "modality": "text",
          "value": "One that is intrinsically rewarding, done for its own sake"
        },
        {
          "modality": "text",
          "value": "One that is automatically adjusted, scaled to the learner's skill"
        },
        {
          "modality": "text",
          "value": "One that is externally rewarded, pursued for a points or prize payoff"
        },
        {
          "modality": "text",
          "value": "One that is cooperatively pursued, done alongside other learners"
        }
      ],
      "correctIndex": 0,
      "explanation": "Autotelic means intrinsically rewarding — done for itself, not an external payoff, and the engagement from which flow emerges. Chasing points or prizes is the extrinsic opposite.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1drbudl1k4a33n"
    },
    {
      "id": "ot-sdt-5",
      "shape": "mcq",
      "tags": [
        "overjustification",
        "intrinsic",
        "apply"
      ],
      "prompt": {
        "modality": "text",
        "value": "Adding prize money to a hobby someone already loves can reduce their desire to do it. What is this called?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The challenge-skill balance"
        },
        {
          "modality": "text",
          "value": "The reinforcement schedule"
        },
        {
          "modality": "text",
          "value": "The mastery-framing mechanic"
        },
        {
          "modality": "text",
          "value": "The overjustification effect"
        }
      ],
      "correctIndex": 3,
      "explanation": "The overjustification effect: external rewards for an already-intrinsically-motivating task can undermine intrinsic motivation. The challenge-skill balance is flow's precondition, reinforcement schedules are Skinner's reward timing, and mastery framing treats failure as data.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "gn3d731fawfmd"
    },
    {
      "id": "ot-theorists-pavlov-1",
      "shape": "mcq",
      "tags": [
        "behaviorism",
        "theorists"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which theorist was the Russian physiologist whose salivating dogs revealed classical conditioning?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Lev Vygotsky"
        },
        {
          "modality": "text",
          "value": "Ivan Pavlov"
        },
        {
          "modality": "text",
          "value": "John Dewey"
        },
        {
          "modality": "text",
          "value": "B.F. Skinner"
        }
      ],
      "correctIndex": 1,
      "explanation": "Pavlov was the Russian physiologist whose salivating dogs revealed classical conditioning. Skinner is the other behaviorist, but his work was on operant conditioning — reinforcement shaping voluntary behavior.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "63eqbs253w5k"
    },
    {
      "id": "ot-theorists-skinner-2",
      "shape": "mcq",
      "tags": [
        "behaviorism",
        "operant-conditioning"
      ],
      "prompt": {
        "modality": "text",
        "value": "Who studied how reinforcement shapes voluntary behavior (operant conditioning) and built the first \"teaching machines\"?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Ivan Pavlov"
        },
        {
          "modality": "text",
          "value": "George Siemens"
        },
        {
          "modality": "text",
          "value": "B.F. Skinner"
        },
        {
          "modality": "text",
          "value": "Jean Piaget"
        }
      ],
      "correctIndex": 2,
      "explanation": "Skinner studied operant conditioning — reinforcement shaping voluntary behavior — and built the first teaching machines. Pavlov's conditioning was classical (reflexive), not operant.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "s5djq8jtfstk"
    },
    {
      "id": "ot-theorists-piaget-3",
      "shape": "mcq",
      "tags": [
        "constructivism",
        "development"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which theorist mapped four stages of children's cognitive development and described how we assimilate and accommodate new information?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Lev Vygotsky"
        },
        {
          "modality": "text",
          "value": "Benjamin Bloom"
        },
        {
          "modality": "text",
          "value": "John Dewey"
        },
        {
          "modality": "text",
          "value": "Jean Piaget"
        }
      ],
      "correctIndex": 3,
      "explanation": "Piaget mapped the four stages of children's cognitive development and described assimilation and accommodation. Vygotsky is the other constructivist, but his contribution was the social view of learning.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "3abgyg1w2dtg0"
    },
    {
      "id": "ot-theorists-vygotsky-4",
      "shape": "mcq",
      "tags": [
        "constructivism",
        "vygotsky"
      ],
      "prompt": {
        "modality": "text",
        "value": "What was Lev Vygotsky's contribution to learning theory?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Mapping the stages of children's cognitive development"
        },
        {
          "modality": "text",
          "value": "Showing that the mind codes words and images separately"
        },
        {
          "modality": "text",
          "value": "Defining the gap between solo and supported performance"
        },
        {
          "modality": "text",
          "value": "Insisting that genuine learning requires learning by doing"
        }
      ],
      "correctIndex": 2,
      "explanation": "Vygotsky, who argued that learning is social, defined the gap between solo and supported performance — the Zone of Proximal Development. The stages of cognitive development are Piaget's, the separate coding of words and images is Paivio's, and \"learn by doing\" is Dewey's.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "jqdyv31v1ijkd"
    },
    {
      "id": "ot-theorists-dewey-5",
      "shape": "mcq",
      "tags": [
        "constructivism",
        "dewey"
      ],
      "prompt": {
        "modality": "text",
        "value": "A teacher rebuilds a unit around hands-on projects, saying students \"learn best by doing.\" Which theorist's principle is she applying?"
      },
      "options": [
        {
          "modality": "text",
          "value": "B.F. Skinner"
        },
        {
          "modality": "text",
          "value": "Jean Piaget"
        },
        {
          "modality": "text",
          "value": "Ivan Pavlov"
        },
        {
          "modality": "text",
          "value": "John Dewey"
        }
      ],
      "correctIndex": 3,
      "explanation": "\"Learn best by doing\" is Dewey, the great American pragmatist. Piaget also studied active meaning-making, but the learn-by-doing slogan is Dewey's.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1xq6e2donqzzr"
    },
    {
      "id": "ot-measurers-ebbinghaus-1",
      "shape": "mcq",
      "tags": [
        "memory",
        "ebbinghaus"
      ],
      "prompt": {
        "modality": "text",
        "value": "Who memorized nonsense syllables in the 1880s and produced the first curve of forgetting?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Allan Paivio"
        },
        {
          "modality": "text",
          "value": "Benjamin Bloom"
        },
        {
          "modality": "text",
          "value": "Hermann Ebbinghaus"
        },
        {
          "modality": "text",
          "value": "Mihaly Csikszentmihalyi"
        }
      ],
      "correctIndex": 2,
      "explanation": "Ebbinghaus used nonsense syllables in the 1880s to chart the first forgetting curve. Paivio is also a memory researcher, but his contribution was dual coding — words and images as separate codes.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "z6csig19gizb4"
    },
    {
      "id": "ot-measurers-csik-2",
      "shape": "mcq",
      "tags": [
        "flow",
        "theorists"
      ],
      "prompt": {
        "modality": "text",
        "value": "A game designer tunes difficulty to rise with the player's growing skill, chasing a state of total absorption. Which researcher named that state?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Hermann Ebbinghaus"
        },
        {
          "modality": "text",
          "value": "Benjamin Bloom"
        },
        {
          "modality": "text",
          "value": "George Siemens"
        },
        {
          "modality": "text",
          "value": "Mihaly Csikszentmihalyi"
        }
      ],
      "correctIndex": 3,
      "explanation": "Csikszentmihalyi named Flow — total absorption where challenge meets skill, exactly what the designer is tuning for. Siemens is a modern figure too, but he updated learning theory for networks and devices.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "t09yim18n09g2"
    },
    {
      "id": "ot-measurers-siemens-3",
      "shape": "mcq",
      "tags": [
        "connectivism",
        "modern"
      ],
      "prompt": {
        "modality": "text",
        "value": "What did George Siemens contribute to learning theory?"
      },
      "options": [
        {
          "modality": "text",
          "value": "A finding that one-to-one tutoring is worth two standard deviations",
          "short": "Tutoring worth two standard deviations"
        },
        {
          "modality": "text",
          "value": "A curve of forgetting charted from nonsense syllables",
          "short": "Nonsense-syllable forgetting curve"
        },
        {
          "modality": "text",
          "value": "A model in which words and images are coded as two channels",
          "short": "Words and images as two channels"
        },
        {
          "modality": "text",
          "value": "A view of knowledge as distributed across networks and devices",
          "short": "Knowledge distributed across networks"
        }
      ],
      "correctIndex": 3,
      "explanation": "Siemens updated learning theory for a world of networks and devices — connectivism. The two-standard-deviation tutoring finding is Bloom's, the nonsense-syllable forgetting curve is Ebbinghaus's, and words and images as two channels is Paivio's dual coding.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "kralcj1n6mzgp"
    },
    {
      "id": "ot-measurers-khan-4",
      "shape": "mcq",
      "tags": [
        "modern",
        "khan"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which former hedge-fund analyst turned online tutoring into a global nonprofit and wrote a 2024 manifesto for AI in education?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Benjamin Bloom"
        },
        {
          "modality": "text",
          "value": "Sal Khan"
        },
        {
          "modality": "text",
          "value": "George Siemens"
        },
        {
          "modality": "text",
          "value": "John Dewey"
        }
      ],
      "correctIndex": 1,
      "explanation": "Sal Khan, a former hedge-fund analyst, built a global tutoring nonprofit and published a 2024 manifesto for AI in education. Siemens also works on digital-age learning, but from networks theory, not tutoring at scale.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1o9sbhg11jod0c"
    },
    {
      "id": "ot-memory-fw-curve-1",
      "shape": "mcq",
      "tags": [
        "memory",
        "forgetting"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which framework names the steep decay of unreviewed memory?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The Forgetting Curve"
        },
        {
          "modality": "text",
          "value": "Spaced Repetition"
        },
        {
          "modality": "text",
          "value": "The Testing Effect"
        },
        {
          "modality": "text",
          "value": "Cognitive Load Theory"
        }
      ],
      "correctIndex": 0,
      "explanation": "The Forgetting Curve is the steep decay of unreviewed memory, first charted by Ebbinghaus. Spaced Repetition is the countermeasure — the scheduling of reviews — not the decay itself.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "14ag2a81jxm70w"
    },
    {
      "id": "ot-memory-fw-spacing-2",
      "shape": "mcq",
      "tags": [
        "spacing",
        "memory"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which framework works by scheduling reviews at expanding intervals?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The Forgetting Curve"
        },
        {
          "modality": "text",
          "value": "Dual Coding Theory"
        },
        {
          "modality": "text",
          "value": "Spaced Repetition"
        },
        {
          "modality": "text",
          "value": "The Testing Effect"
        }
      ],
      "correctIndex": 2,
      "explanation": "Spaced Repetition schedules reviews at expanding intervals, which is why it defeats the Forgetting Curve. The Testing Effect is about how you review (retrieval), not when.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1s099jvjyc9bl"
    },
    {
      "id": "ot-memory-fw-zpd-3",
      "shape": "mcq",
      "tags": [
        "zpd",
        "constructivism"
      ],
      "prompt": {
        "modality": "text",
        "value": "A student can solve a problem with a tutor's hints but not on her own. Which framework names that productive band?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Cognitive Load Theory"
        },
        {
          "modality": "text",
          "value": "Self-Determination Theory"
        },
        {
          "modality": "text",
          "value": "Zone of Proximal Development"
        },
        {
          "modality": "text",
          "value": "Conditions of Learning"
        }
      ],
      "correctIndex": 2,
      "explanation": "The Zone of Proximal Development is the productive band between independent and supported performance — exactly this gap. Cognitive Load and Dual Coding describe how working memory handles material, and the Testing Effect describes retrieval; only the ZPD is about support from another person.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "52ziizhhm4yp"
    },
    {
      "id": "ot-memory-fw-testing-4",
      "shape": "mcq",
      "tags": [
        "testing-effect",
        "memory"
      ],
      "prompt": {
        "modality": "text",
        "value": "What is the finding known as the Testing Effect?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Reviews spaced at expanding intervals beat one crammed session"
        },
        {
          "modality": "text",
          "value": "Pulling information out of memory beats re-reading it"
        },
        {
          "modality": "text",
          "value": "Pairing words with images beats presenting either one alone"
        },
        {
          "modality": "text",
          "value": "Challenge matched to skill beats challenge set too high or low"
        }
      ],
      "correctIndex": 1,
      "explanation": "The Testing Effect — retrieval practice — is the finding that pulling information out of memory, as in self-quizzing, beats re-reading. Expanding intervals are Spaced Repetition, words plus images is Dual Coding, and challenge matched to skill is Flow.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1hm9zg3oog34p"
    },
    {
      "id": "ot-cog-fw-blooms-1",
      "shape": "mcq",
      "tags": [
        "blooms-taxonomy",
        "frameworks"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which framework is the six-level ladder of cognitive skill running from Remember up to Create?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The Kirkpatrick Model"
        },
        {
          "modality": "text",
          "value": "Merrill's Principles"
        },
        {
          "modality": "text",
          "value": "Bloom's Taxonomy"
        },
        {
          "modality": "text",
          "value": "The Affective Domain"
        }
      ],
      "correctIndex": 2,
      "explanation": "Bloom's Taxonomy is the six-level hierarchy of cognitive objectives, Remember to Create. The affective domain is Bloom's team's five-level companion (Receiving to Characterizing), and the Kirkpatrick Model's four levels evaluate training rather than rank learner thinking.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1m269saht0t2"
    },
    {
      "id": "ot-cog-fw-load-2",
      "shape": "mcq",
      "tags": [
        "cognitive-load",
        "working-memory"
      ],
      "prompt": {
        "modality": "text",
        "value": "A lesson piles twelve new terms onto one dense slide and learners stall out. Which framework best explains the failure?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Cognitive Load Theory"
        },
        {
          "modality": "text",
          "value": "Dual Coding Theory"
        },
        {
          "modality": "text",
          "value": "The Forgetting Curve"
        },
        {
          "modality": "text",
          "value": "The Testing Effect"
        }
      ],
      "correctIndex": 0,
      "explanation": "Cognitive Load Theory is about managing working memory's hard limits — overloading them stalls learning. Dual Coding's two channels (words and images) are a remedy, not the explanation; the Forgetting Curve and Testing Effect concern memory after a lesson, not a stall mid-lesson.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "14ac54wyo7b3s"
    },
    {
      "id": "ot-cog-fw-flow-3",
      "shape": "mcq",
      "tags": [
        "flow",
        "frameworks"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which framework-to-description pairing is correct?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Connectivism — learning held inside the individual mind",
          "short": "Connectivism — learning inside the mind"
        },
        {
          "modality": "text",
          "value": "Flow — effortless immersion when challenge matches skill",
          "short": "Flow — immersion when challenge = skill"
        },
        {
          "modality": "text",
          "value": "Dual Coding Theory — managing working memory's hard limits",
          "short": "Dual Coding — managing working memory"
        },
        {
          "modality": "text",
          "value": "Cognitive Load Theory — steep decay of memory left unreviewed",
          "short": "Cognitive Load — decay of unreviewed memory"
        }
      ],
      "correctIndex": 1,
      "explanation": "Flow is effortless immersion when challenge matches skill. The others are mismatched: managing working memory's limits is Cognitive Load Theory, steep decay of unreviewed memory is the Forgetting Curve, and Connectivism puts learning in networks, not inside the mind.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1enet84vus804"
    },
    {
      "id": "ot-cog-fw-connectivism-4",
      "shape": "mcq",
      "tags": [
        "connectivism",
        "digital-age"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which statement accurately describes Connectivism?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It locates learning in the gap between solo and supported performance",
          "short": "Learning lives between solo and supported"
        },
        {
          "modality": "text",
          "value": "It reframes knowledge as distributed across networks for the digital age",
          "short": "Knowledge spread across networks"
        },
        {
          "modality": "text",
          "value": "It holds that different kinds of learning outcome each demand their own instruction",
          "short": "Each outcome type needs its own teaching"
        },
        {
          "modality": "text",
          "value": "It holds that knowledge built through guided questioning outlasts knowledge merely received",
          "short": "Questioned knowledge outlasts received"
        }
      ],
      "correctIndex": 1,
      "explanation": "Connectivism reframes knowledge as distributed across networks, updating learning theory for the digital age. Siemens and Downes argued that older theories missed learning outside the individual mind, and that knowing where to find information now outweighs knowing it by heart.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1xpmauc14dqfn8"
    },
    {
      "id": "ot-adaptive-als-def",
      "shape": "mcq",
      "tags": [
        "als",
        "adaptive-systems"
      ],
      "prompt": {
        "modality": "text",
        "value": "An Adaptive Learning System dynamically adjusts which three aspects of instruction, based on ongoing learner performance data?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Instructional content, process, and product"
        },
        {
          "modality": "text",
          "value": "Content difficulty, sequence, and modality"
        },
        {
          "modality": "text",
          "value": "Representation, expression, and engagement"
        },
        {
          "modality": "text",
          "value": "Autonomy, competence, and relatedness"
        }
      ],
      "correctIndex": 1,
      "explanation": "An ALS is defined by adjusting content difficulty, sequence, and modality from ongoing performance data. Content, process and product are differentiated instruction's levers; representation, expression and engagement are UDL; autonomy, competence and relatedness are SDT.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "rlmlps118lllc"
    },
    {
      "id": "ot-adaptive-dkt-vs-bkt",
      "shape": "mcq",
      "tags": [
        "dkt",
        "bkt",
        "knowledge-tracing"
      ],
      "prompt": {
        "modality": "text",
        "value": "How does Deep Knowledge Tracing (Piech et al., 2015) differ from Bayesian Knowledge Tracing?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It replaces the learner model with explicit models of the domain and the pedagogy (the other two ITS models)",
          "short": "Models domain & pedagogy, not learner"
        },
        {
          "modality": "text",
          "value": "It replaces hand-crafted probability tables with a recurrent neural network (LSTM) hidden state",
          "short": "Uses an LSTM hidden state, not tables"
        },
        {
          "modality": "text",
          "value": "It replaces per-response updating with a single mastery estimate (a posterior) computed at the end of each unit",
          "short": "One mastery estimate at unit's end"
        },
        {
          "modality": "text",
          "value": "It replaces the neural hidden state with hand-crafted probability tables (one per skill)",
          "short": "Uses hand-built tables, not a network"
        }
      ],
      "correctIndex": 1,
      "explanation": "DKT models learner knowledge as an LSTM hidden state evolving with each interaction, replacing BKT's hand-crafted probability tables. Both model the learner and update after every response, so the domain-and-pedagogy and end-of-unit options fail; the last option is backwards.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1t22je51x5xn8n"
    },
    {
      "id": "ot-adaptive-knowledge-state",
      "shape": "mcq",
      "tags": [
        "knowledge-state",
        "adaptive-systems"
      ],
      "prompt": {
        "modality": "text",
        "value": "A system maintains a model of what one specific learner currently knows and doesn't know, updating it continuously. What is that model called?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Knowledge Graph"
        },
        {
          "modality": "text",
          "value": "Knowledge State"
        },
        {
          "modality": "text",
          "value": "Learner Analytics"
        },
        {
          "modality": "text",
          "value": "Learning Ontology"
        }
      ],
      "correctIndex": 1,
      "explanation": "The Knowledge State is the per-learner model of what is and isn't known, updated continuously. A knowledge graph maps objectives and dependencies, a learning ontology formalizes a domain's concepts, and learner analytics measures and reports data — none is one learner's standing.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "3utnde39yiim"
    },
    {
      "id": "ot-adaptive-sequencing-loop",
      "shape": "mcq",
      "tags": [
        "sequencing",
        "adaptive-systems"
      ],
      "prompt": {
        "modality": "text",
        "value": "Algorithm-Based Sequencing runs a repeating loop. Which step is NOT part of that loop?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Observe the learner's response"
        },
        {
          "modality": "text",
          "value": "Update the estimated knowledge state"
        },
        {
          "modality": "text",
          "value": "Select the optimal next item to present"
        },
        {
          "modality": "text",
          "value": "Award a completion certificate once the unit timer expires"
        }
      ],
      "correctIndex": 3,
      "explanation": "The loop is observe, update state, select next item, repeat. Timer-based certificates are the opposite of algorithmic sequencing, which selects items from the predicted knowledge state.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "hss3x2edvsu2"
    },
    {
      "id": "ot-genai-zero-shot",
      "shape": "mcq",
      "tags": [
        "zero-shot",
        "genai"
      ],
      "prompt": {
        "modality": "text",
        "value": "Zero-Shot Learning (AI) describes an LLM's ability to do what?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Perform a task it was not explicitly trained on, generalizing from broad pre-training",
          "short": "Do an untrained task from pre-training"
        },
        {
          "modality": "text",
          "value": "Master a task after a few labelled examples appear in the prompt, generalizing from those demonstrations",
          "short": "Learn a task from a few prompt examples"
        },
        {
          "modality": "text",
          "value": "Train on data that carries no human-supplied labels, discovering structure in the raw corpus",
          "short": "Learn structure from unlabelled data"
        },
        {
          "modality": "text",
          "value": "Retain every prior learner interaction across sessions, drawing on that history at inference",
          "short": "Recall every past interaction, all sessions"
        }
      ],
      "correctIndex": 0,
      "explanation": "Zero-shot means performing an untrained task by generalizing from pre-training — useful for curriculum on rare subjects. In-prompt examples make it few-shot, learning from unlabelled data is unsupervised training, and remembering past sessions is a memory feature, not zero-shot.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "z89bzg2ias1g"
    },
    {
      "id": "ot-genai-prompt-eng",
      "shape": "mcq",
      "tags": [
        "prompt-engineering",
        "genai"
      ],
      "prompt": {
        "modality": "text",
        "value": "Prompt Engineering, a core skill for edtech builders working with foundation models, is best described as which activity?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Designing the inputs given to LLMs so they produce the desired instructional outputs",
          "short": "Designing LLM inputs to get desired outputs"
        },
        {
          "modality": "text",
          "value": "Fine-tuning a model's weights on curriculum data so it produces domain-specific outputs",
          "short": "Fine-tuning model weights on curriculum data"
        },
        {
          "modality": "text",
          "value": "Ranking pairs of a model's outputs so a separate reward model learns instructional preferences",
          "short": "Ranking outputs to train a reward model"
        },
        {
          "modality": "text",
          "value": "Writing the integration code so a model's outputs are served inside the school's LMS",
          "short": "Coding LLM output delivery into an LMS"
        }
      ],
      "correctIndex": 0,
      "explanation": "Prompt engineering is designing the inputs to LLMs so they produce the desired instructional outputs. Fine-tuning changes the model's weights — a different intervention entirely.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "df6ri9qgfo5v"
    },
    {
      "id": "ot-genai-hitl",
      "shape": "mcq",
      "tags": [
        "hitl",
        "responsible-ai"
      ],
      "prompt": {
        "modality": "text",
        "value": "An edtech team requires a teacher to review and approve every AI-generated quiz before students see it. Which design principle is this?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Adaptive Learning System (ALS)"
        },
        {
          "modality": "text",
          "value": "Human-in-the-Loop (HITL)"
        },
        {
          "modality": "text",
          "value": "Competency-Based Education (CBE)"
        },
        {
          "modality": "text",
          "value": "Problem-Based Learning (PBL)"
        }
      ],
      "correctIndex": 1,
      "explanation": "HITL design has humans review, approve, or override AI outputs before delivery — the standard check against errors in edtech. An ITS is defined by teaching without a human teacher, UDL is a framework for building flexible curricula, and GenAI is the technology whose quizzes the teacher is checking.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "gdx9ag4fl8rk"
    },
    {
      "id": "ot-genai-ontology",
      "shape": "mcq",
      "tags": [
        "ontology",
        "curriculum-graph"
      ],
      "prompt": {
        "modality": "text",
        "value": "How does an Ontology (Learning) relate to a Curriculum Graph?"
      },
      "options": [
        {
          "modality": "text",
          "value": "It represents domain concepts and their relationships, organizing curriculum graphs and recommendations",
          "short": "Maps domain concepts & their relations"
        },
        {
          "modality": "text",
          "value": "It logs each learner's interactions with the graph, scoring its prerequisite edges from that evidence",
          "short": "Logs learner actions to score edges"
        },
        {
          "modality": "text",
          "value": "It is the interoperability standard for the graph, carrying its objectives between LMS platforms",
          "short": "Swaps graph data between LMS platforms"
        },
        {
          "modality": "text",
          "value": "It is the per-learner layer of the graph, tracking what one student has mastered up to now",
          "short": "Tracks what one learner has mastered"
        }
      ],
      "correctIndex": 0,
      "explanation": "An ontology formalizes knowledge and concept relationships in a domain, and is used to organize curriculum graphs and content recommendations. The per-learner record of mastery is the Knowledge State, and the interoperability standard for learner data is xAPI, not an ontology.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "o0hjcgnx9qvs"
    },
    {
      "id": "ot-pedagogy-metacognition",
      "shape": "mcq",
      "tags": [
        "metacognition",
        "ai-tutors"
      ],
      "prompt": {
        "modality": "text",
        "value": "AI tutors like Khanmigo prompt students to explain their reasoning rather than just supplying answers. Which capacity is this designed to foster?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Transfer of learning"
        },
        {
          "modality": "text",
          "value": "Working memory"
        },
        {
          "modality": "text",
          "value": "Intrinsic motivation"
        },
        {
          "modality": "text",
          "value": "Metacognition"
        }
      ],
      "correctIndex": 3,
      "explanation": "Metacognition is thinking about one's own thinking — awareness of one's learning process, gaps, and strategies. Prompting learners to explain their reasoning targets exactly that awareness.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "8uc5kgx58dsg"
    },
    {
      "id": "ot-pedagogy-diff-vs-personal",
      "shape": "mcq",
      "tags": [
        "differentiated-instruction",
        "personalized-learning"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which statement describes Differentiated Instruction rather than Personalized Learning?"
      },
      "options": [
        {
          "modality": "text",
          "value": "An adaptive system tailors pace, sequence, and modality to each learner's goals and learning style",
          "short": "Adaptive system tailors pace to each learner"
        },
        {
          "modality": "text",
          "value": "A teacher tailors content, process, or product to individual needs within a group setting",
          "short": "Teacher tailors work to needs within a group"
        },
        {
          "modality": "text",
          "value": "A teacher tailors each learner's rate of progression to demonstrated mastery rather than time spent",
          "short": "Teacher paces each learner by mastery shown"
        },
        {
          "modality": "text",
          "value": "A tutor tailors content, process, and product to a single learner in private tutoring",
          "short": "Tutor tailors work to one learner privately"
        }
      ],
      "correctIndex": 1,
      "explanation": "Differentiated Instruction is the classroom precursor: teacher-led tailoring within a group. Tailoring pace, content, sequence, and modality to the individual is Personalized Learning, the broader term.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1kyxdj1150md27"
    },
    {
      "id": "ot-pedagogy-scaffolding-zpd",
      "shape": "mcq",
      "tags": [
        "scaffolding",
        "vygotsky"
      ],
      "prompt": {
        "modality": "text",
        "value": "A Scaffolded Curriculum gives support at each level and fades assistance as competence grows, directly implementing whose idea?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Bloom's taxonomy of cognitive objectives"
        },
        {
          "modality": "text",
          "value": "Vygotsky's zone of proximal development"
        },
        {
          "modality": "text",
          "value": "Piaget's stages of cognitive development"
        },
        {
          "modality": "text",
          "value": "Csikszentmihalyi's theory of flow"
        }
      ],
      "correctIndex": 1,
      "explanation": "Scaffolding that fades as competence grows is a direct implementation of Vygotsky's zone of proximal development — the gap between solo and supported performance.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1d8w9oz14mzb1d"
    },
    {
      "id": "ot-pedagogy-not-accurate",
      "shape": "mcq",
      "tags": [
        "multimodal",
        "pbl",
        "cbe"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which statement about these pedagogy and instruction terms is NOT accurate?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Multimodal Learning delivers one modality at a time so working memory is never overloaded",
          "short": "Multimodal: one modality at a time"
        },
        {
          "modality": "text",
          "value": "Microlearning builds every short, focused burst around one learning objective only",
          "short": "Microlearning: one objective per burst"
        },
        {
          "modality": "text",
          "value": "Competency-Based Education counts demonstrated mastery, never time spent, toward progression",
          "short": "CBE counts mastery rather than time spent"
        },
        {
          "modality": "text",
          "value": "Problem-Based Learning has students learn by investigating an authentic, open-ended problem",
          "short": "PBL: learn by investigating a real problem"
        }
      ],
      "correctIndex": 0,
      "explanation": "Multimodal Learning engages several sensory channels — visual, auditory, kinesthetic — together to deepen encoding; it does not isolate them one at a time. The other three statements are accurate.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "unpm8euam0ve"
    },
    {
      "id": "ot-ls-working-memory",
      "shape": "mcq",
      "tags": [
        "working-memory",
        "cognitive-load"
      ],
      "prompt": {
        "modality": "text",
        "value": "Working memory temporarily holds and manipulates information during active processing. Roughly how many items can it handle at once?"
      },
      "options": [
        {
          "modality": "text",
          "value": "About 3±1"
        },
        {
          "modality": "text",
          "value": "About 20±5"
        },
        {
          "modality": "text",
          "value": "About 12±2"
        },
        {
          "modality": "text",
          "value": "About 7±2"
        }
      ],
      "correctIndex": 3,
      "explanation": "Working memory handles roughly 7±2 items at a time, and cognitive load theory is built on that limit — overload it and learning degrades.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "nx6gqi1goy4pi"
    },
    {
      "id": "ot-ls-chunking",
      "shape": "mcq",
      "tags": [
        "chunking",
        "cognitive-load"
      ],
      "prompt": {
        "modality": "text",
        "value": "A designer splits a 12-digit code into three groups of four so learners can hold it more easily. Which technique is this?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Chunking"
        },
        {
          "modality": "text",
          "value": "Scaffolding"
        },
        {
          "modality": "text",
          "value": "Multimodal learning"
        },
        {
          "modality": "text",
          "value": "Transfer of learning"
        }
      ],
      "correctIndex": 0,
      "explanation": "Chunking breaks complex information into smaller, manageable units to reduce cognitive load and improve encoding — the direct response to working memory's limits.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "k106lbbjfwt"
    },
    {
      "id": "ot-ls-not-accurate",
      "shape": "mcq",
      "tags": [
        "transfer",
        "edtech",
        "learning-science"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which statement about these learning-science terms is NOT accurate?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Self-Determination Theory was put forward by Deci & Ryan in 1985",
          "short": "SDT proposed by Deci & Ryan (1985)"
        },
        {
          "modality": "text",
          "value": "EdTech is any technology used to facilitate or enhance learning",
          "short": "EdTech: any tech that aids learning"
        },
        {
          "modality": "text",
          "value": "Transfer of Learning means repeating material until it can be recalled verbatim",
          "short": "Transfer: repeat until verbatim recall"
        },
        {
          "modality": "text",
          "value": "Working memory temporarily holds and manipulates information during active processing",
          "short": "Working memory holds info while processing"
        }
      ],
      "correctIndex": 2,
      "explanation": "Transfer of Learning is applying knowledge or skills from one context to new, different ones — the goal shallow memorization fails to reach. Verbatim repetition is the opposite of transfer. The other three are accurate.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "w3d2ndzqxy7n"
    },
    {
      "id": "ot-ls-pck",
      "shape": "mcq",
      "tags": [
        "pck",
        "shulman"
      ],
      "prompt": {
        "modality": "text",
        "value": "Lee Shulman's 1986 concept of Pedagogical Content Knowledge names which kind of knowledge?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Deep expertise in a subject itself, distinct from any skill at teaching that subject",
          "short": "Subject expertise, not how to teach it"
        },
        {
          "modality": "text",
          "value": "Knowing how to teach a specific subject, distinct from knowing the subject itself",
          "short": "How to teach a subject, not just know it"
        },
        {
          "modality": "text",
          "value": "General skill at managing a classroom, distinct from expertise in any one subject",
          "short": "Classroom management, apart from subject"
        },
        {
          "modality": "text",
          "value": "Command of a grade's curriculum standards, distinct from mastery of the subject itself",
          "short": "Grade standards, apart from the subject"
        }
      ],
      "correctIndex": 1,
      "explanation": "PCK distinguishes knowing a subject from knowing how to teach it: a chemistry expert and a chemistry teacher have different knowledge, and PCK names what the teacher has that the expert may lack.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1nr9l1t6hf62z"
    },
    {
      "id": "ot-assess-formative",
      "shape": "mcq",
      "tags": [
        "formative-assessment",
        "assessment"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which of these is an example of Formative Assessment?"
      },
      "options": [
        {
          "modality": "text",
          "value": "A final project graded once the course ends that fixes each student's overall mark",
          "short": "Final project graded after the course ends"
        },
        {
          "modality": "text",
          "value": "A certification test at the close of training that attests to a candidate's competence",
          "short": "Cert test after training attests competence"
        },
        {
          "modality": "text",
          "value": "A low-stakes retrieval quiz during a unit that lets instruction adjust",
          "short": "Low-stakes quiz mid-unit to adjust teaching"
        },
        {
          "modality": "text",
          "value": "A high-stakes midterm exam partway through a unit that counts toward the final grade",
          "short": "High-stakes midterm counting toward grade"
        }
      ],
      "correctIndex": 2,
      "explanation": "Formative assessment happens during learning — low-stakes quizzes, check-ins, retrieval prompts — giving feedback so instruction can adjust.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "nutxwzpauq81"
    },
    {
      "id": "ot-assess-xapi",
      "shape": "mcq",
      "tags": [
        "xapi",
        "standards"
      ],
      "prompt": {
        "modality": "text",
        "value": "The xAPI / Tin Can API standard exists to do what?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Estimate the probability a learner has mastered a skill, so the next item can be chosen",
          "short": "Estimate mastery to choose the next item"
        },
        {
          "modality": "text",
          "value": "Generate quiz items from a source document, so assessments can be produced at scale",
          "short": "Auto-generate quiz items at scale"
        },
        {
          "modality": "text",
          "value": "Capture experience statements across all learning contexts, so analytics follow the learner",
          "short": "Capture experience data across all contexts"
        },
        {
          "modality": "text",
          "value": "Represent learning objectives and their prerequisites, so optimal paths can be found",
          "short": "Map objectives & prerequisites into paths"
        }
      ],
      "correctIndex": 2,
      "explanation": "xAPI is the interoperability standard that captures experience statements wherever learning happens, not just inside an LMS. Mastery probability estimation is BKT's job; dependencies are a curriculum graph's.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "fab0u717kybl1"
    },
    {
      "id": "ot-assess-learner-analytics",
      "shape": "mcq",
      "tags": [
        "learner-analytics",
        "data"
      ],
      "prompt": {
        "modality": "text",
        "value": "Learner Analytics is defined as which of the following?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Capturing, storing, and exchanging experience statements across systems, to keep learning records portable",
          "short": "Exchanging learning records across systems"
        },
        {
          "modality": "text",
          "value": "Rating reaction, learning, behavior, and results after training, to judge whether it worked",
          "short": "Rating four levels to judge if training worked"
        },
        {
          "modality": "text",
          "value": "Measuring, collecting, analyzing, and reporting data about learners and their contexts, to optimize learning",
          "short": "Analyzing learner data to improve learning"
        },
        {
          "modality": "text",
          "value": "Outlining objectives, content, sequence, and timeline for a course, to plan what is taught when",
          "short": "Outlining a course's objectives and timeline"
        }
      ],
      "correctIndex": 2,
      "explanation": "Learner Analytics covers measuring, collecting, analyzing, and reporting data about learners and their contexts to optimize learning. The exchange standard is xAPI; the four-level framework is Kirkpatrick.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1x5fks1r5jofn"
    },
    {
      "id": "ot-assess-not-accurate",
      "shape": "mcq",
      "tags": [
        "mooc",
        "steam",
        "syllabus"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which statement about these assessment, data, and standards terms is NOT accurate?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Coursera, edX, and Udemy established the MOOC model",
          "short": "MOOC model = Coursera/edX/Udemy"
        },
        {
          "modality": "text",
          "value": "A syllabus / curriculum map outlines objectives, content, sequence, and timeline",
          "short": "Syllabus = objectives + sequence"
        },
        {
          "modality": "text",
          "value": "A MOOC is a large-scale online course open to unlimited participation",
          "short": "MOOC = massive open online course"
        },
        {
          "modality": "text",
          "value": "STEAM adds Assessment to the STEM disciplines",
          "short": "STEAM = STEM plus Assessment"
        }
      ],
      "correctIndex": 3,
      "explanation": "STEAM adds Arts — Science, Technology, Engineering, Arts, Mathematics — not Assessment. The other three statements match the definitions exactly.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1nmv8wswf2570"
    },
    {
      "id": "fi-ot-modes-2",
      "tags": [
        "passive-learning",
        "modes"
      ],
      "title": "Re-reading Isn't Studying",
      "body": "Re-reading a chapter you've already highlighted counts as passive learning, not active or interactive — flashcards count as active retrieval, while teaching or debating the material counts as interactive.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "student rereading highlighted textbook",
        "imagePrompt": "A student sitting at a desk, passively rereading a textbook page covered in yellow highlighter marks, chin resting on hand, looking drowsy.",
        "alt": "Re-reading Isn't Studying",
        "depictable": true,
        "credit": "Pexels · Tannishq Giri · Pexels License",
        "creditUrl": "https://www.pexels.com/photo/study-materials-on-human-skeletal-system-37065064/",
        "subject": "a top-down flat lay of an anatomy textbook page (Skeletal System, Figure 17.6 skull diagram) heavily marked with orange and yellow highlighter, handwritten margin notes, black-framed glasses and two pens on top, a second open book at right",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/fi-ot-modes-2.webp"
      },
      "uid": "ywp35jxpgy5h"
    },
    {
      "id": "fi-ot-hebbian-2",
      "tags": [
        "hebbian",
        "synapse"
      ],
      "title": "Synapses Thicken With Practice",
      "body": "When repeated co-activation strengthens a learned pattern, the change is physical: the synapse connecting the neurons thickens and the signal between them travels faster.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "neurons synapse connection glowing",
        "imagePrompt": "A close-up scientific illustration of two neurons connecting at a synapse, the connection point glowing and thickened to show a strengthened neural pathway.",
        "alt": "Synapses Thicken With Practice",
        "depictable": true,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:4_spill_2_knowing-neurons2.jpg",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/fi-ot-hebbian-2.webp"
      },
      "uid": "8qorp63zvis6"
    },
    {
      "id": "fi-ot-hebbian-5",
      "tags": [
        "hebbian",
        "passive-learning",
        "apply"
      ],
      "title": "Weak Wiring Without Recall",
      "body": "A student who rewatches a lecture five times but never quizzes herself builds only weak connections — without retrieval, the relevant neurons never fire, so the wiring stays weak.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "student watching lecture passively",
        "imagePrompt": "A student sitting passively in front of a laptop playing a recorded lecture, glassy-eyed and unengaged, with no notes or quiz materials nearby.",
        "alt": "Weak Wiring Without Recall",
        "depictable": true
      },
      "uid": "21o5t7sxupb5"
    },
    {
      "id": "fi-ot-forget-1",
      "tags": [
        "forgetting-curve",
        "numbers"
      ],
      "title": "The First 30 Minutes",
      "body": "Without any review, roughly half of what you just learned is gone within 30 minutes — the steep opening plunge of the forgetting curve.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "student confused own notes",
        "imagePrompt": "A student sitting just after class, staring blankly at their own notes with a puzzled expression, already struggling to recall what was just taught, no visible text on the page.",
        "alt": "The First 30 Minutes",
        "depictable": false,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:RES_Student_Housing.jpg",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/fi-ot-forget-1.webp"
      },
      "uid": "117yop3egql6l"
    },
    {
      "id": "fi-ot-forget-2",
      "tags": [
        "forgetting-curve",
        "numbers"
      ],
      "title": "A Day Without Review",
      "body": "Left unreviewed, about 75% of newly learned information is gone within 24 hours — the forgetting curve's decay continues well past the first half hour.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "student next-day forgetting notes",
        "imagePrompt": "A student the next morning, sitting at a desk with yesterday's notes, rubbing their eyes and looking uncertain, evoking memory faded overnight.",
        "alt": "A Day Without Review",
        "depictable": false,
        "credit": "Pexels · A person's hand writing in a notebook on a sunny day, showing detailed cursive notes.",
        "creditUrl": "https://www.pexels.com/photo/close-up-of-handwriting-in-a-notebook-under-daylight-37822450/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/fi-ot-forget-2.webp"
      },
      "uid": "uamhpu4ufvna"
    },
    {
      "id": "fi-mcq-rw-l1-p2-forgetting-spacing",
      "tags": [
        "forgetting-curve",
        "spaced-repetition",
        "memory"
      ],
      "title": "Time Your First Review",
      "body": "Because the forgetting curve drops fastest right after learning, your first review is most valuable when it happens soon afterward — timing matters as much as total study time, and it's the basis for spaced repetition's expanding intervals.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "increasing spaced review gaps",
        "imagePrompt": "A row of small glowing light bulbs spaced increasingly farther apart along a path, each one glowing a bit brighter than the last, evoking a first review timed soon after learning followed by progressively longer gaps, no visible text or numbers.",
        "alt": "Time Your First Review",
        "depictable": false,
        "credit": "AI-generated (gpt-image-1.5)",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/fi-mcq-rw-l1-p2-forgetting-spacing.webp"
      },
      "uid": "12j0ywpbmxws3"
    },
    {
      "id": "fi-ot-spacing-2",
      "tags": [
        "spaced-repetition",
        "mechanism"
      ],
      "title": "Beat Cramming With Timing",
      "body": "Reviewing material right before you'd forget it beats cramming the same amount of time in, because retrieving a memory at its weakest point forces more effortful encoding and resets the decay clock.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "student cramming late night",
        "imagePrompt": "A tired student surrounded by scattered papers and coffee cups, cramming at a desk late at night under a single lamp.",
        "alt": "Beat Cramming With Timing",
        "depictable": false,
        "credit": "Pexels · A dedicated student studying late at night in a library setting, surrounded by books.",
        "creditUrl": "https://www.pexels.com/photo/a-woman-sitting-on-a-chair-while-working-at-night-8085249/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/fi-ot-spacing-2.webp"
      },
      "uid": "1u08bjtmw35mj"
    },
    {
      "id": "fi-lt-mcq-mit-implication",
      "tags": [
        "retrieval",
        "testing-effect",
        "edtech"
      ],
      "title": "MIT's Low-Stakes Quiz Rule",
      "body": "MIT Open Learning draws a simple, practical implication from the testing effect: give students frequent low-stakes quizzes, since each one triggers retrieval and helps solidify learning.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "students classroom short quiz",
        "imagePrompt": "A classroom of students filling out a brief quiz on paper at their desks in a relaxed atmosphere, evoking a low-stakes, frequent quiz rather than a major exam.",
        "alt": "MIT's Low-Stakes Quiz Rule",
        "depictable": true,
        "credit": "Pexels · A classroom setting with a teacher proctoring an exam, students focused on their tests.",
        "creditUrl": "https://www.pexels.com/photo/teacher-proctoring-his-students-during-an-examination-7092339/",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/fi-lt-mcq-mit-implication.webp"
      },
      "uid": "ozrbg01vcnm0g"
    },
    {
      "id": "fi-ot-retrieval-2",
      "tags": [
        "karpicke-roediger",
        "evidence"
      ],
      "title": "A Week Later, Retrieval Wins",
      "body": "Karpicke and Roediger's 2008 study found that students who practiced retrieval retained significantly more material a week later than students who simply restudied the same material the same number of times.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "student recalling flashcard memory",
        "imagePrompt": "A student holding up a flashcard with eyes closed, trying to recall the answer from memory, a stack of other flashcards on the desk.",
        "alt": "A Week Later, Retrieval Wins",
        "depictable": false,
        "credit": "AI-generated (gpt-image-1.5)",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/fi-ot-retrieval-2.webp"
      },
      "uid": "yk7zwj2fwnw"
    },
    {
      "id": "fi-ot-retrieval-3",
      "tags": [
        "roediger-butler",
        "evidence"
      ],
      "title": "Retrieval Works Everywhere",
      "body": "A 2011 study by Roediger and Butler confirmed that retrieval practice plays a critical role in long-term retention across a wide range of material types, not just vocabulary.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "varied subjects study flashcards",
        "imagePrompt": "A desk scattered with different study materials, a science diagram, a language vocabulary card, and a history timeline card, evoking retrieval practice applied across many subjects, no legible text.",
        "alt": "Retrieval Works Everywhere",
        "depictable": false,
        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:VariedIndustriesBuildingEastPanamaCaliforniaExpo1915.jpg",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/fi-ot-retrieval-3.webp"
      },
      "uid": "ea8gr414t0bts"
    },
    {
      "id": "fi-ot-retrieval-4",
      "tags": [
        "production-effect",
        "difficulty"
      ],
      "title": "The Sweet Spot for Recall",
      "body": "Under the production effect, retrieval practice produces its biggest memory gains when the recall is difficult but ultimately successful — easy retrieval builds far weaker memory traces.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "student straining to recall",
        "imagePrompt": "A student pausing mid-writing with eyes closed and brow slightly furrowed, straining to recall an answer before it clicks, pencil hovering over the paper.",
        "alt": "The Sweet Spot for Recall",
        "depictable": false,
        "credit": "AI-generated (gpt-image-1.5)",
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/fi-ot-retrieval-4.webp"
      },
      "uid": "ltth3cm5knuo"
    },
    {
      "id": "fi-ot-behaviorism-founders-1",
      "tags": [
        "skinner",
        "behaviorism",
        "pairs"
      ],
      "title": "Skinner: Operant Conditioning",
      "body": "B.F. Skinner is behaviorism's pioneer of operant conditioning — the principle that behavior is shaped by its consequences, distinct from Pavlov's classical conditioning or Watson's early behaviorism.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "Skinner box conditioning apparatus",
        "imagePrompt": "A vintage-style Skinner box apparatus, a small chamber with a lever and food dispenser, used in operant conditioning experiments, with a rat inside.",
        "alt": "Skinner: Operant Conditioning",
        "depictable": true,
        "url": "https://cdn.recurxive.com/packs/learning-theory/images/fi-ot-behaviorism-founders-1.webp",
        "credit": "Pexels · File:First Map of Skinner.png",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:First_Map_of_Skinner.png"
      },
      "uid": "1cgdlx0s8ozmk"
    },
    {
      "id": "fi-ot-behaviorism-founders-2",
      "tags": [
        "pavlov",
        "classical-conditioning"
      ],
      "title": "Pavlov's Bell and Drool",
      "body": "Pavlov paired a bell with food until dogs salivated at the bell alone — demonstrating classical conditioning, in which a neutral stimulus paired with a natural one comes to trigger the response by itself.",
      "shape": "fact",
      "illustration": {
        "imageSearchTerm": "Pavlov dog bell experiment",
        "imagePrompt": "A vintage early-1900s laboratory scene with a dog on a leash beside a small bell and a bowl, evoking Pavlov's classical conditioning experiment.",
        "alt": "Pavlov's Bell and Drool",
        "depictable": true,
        "credit": "Wikimedia Commons · see source",
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      "tags": [
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      "title": "Assimilation: Same Old Schema",
      "body": "When a child who already knows 'dog' sees a new breed and simply calls it a dog too, that's assimilation — fitting new information into an existing schema without changing it.",
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      "tags": [
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      "title": "Accommodation: Schema Under Revision",
      "body": "Accommodation is the opposite move: when new information contradicts an existing schema, the schema itself gets revised to fit it — a more effortful process than simply assimilating.",
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      "tags": [
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      "title": "Working Memory's Hard Limit",
      "body": "George Miller's landmark 1956 paper established that working memory holds only about 7 plus-or-minus 2 chunks at once — a hard capacity limit that has shaped instructional design ever since.",
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      "tags": [
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        "apply"
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      "title": "Four Digits Become One Chunk",
      "body": "Turning the digits 1-4-9-2 into the single meaningful unit '1492' is chunking: it frees up working-memory slots by grouping raw items into one chunk instead of several.",
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      "tags": [
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      "title": "The More Knowledgeable Other",
      "body": "In Vygotsky's zone of proximal development, a 'more knowledgeable other' — a teacher, parent, or more capable peer — supplies the scaffolding that lets a learner accomplish more than they could alone.",
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      "tags": [
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      "title": "Dewey: Learn By Doing",
      "body": "John Dewey's pragmatic constructivism is defined by 'learn by doing' — authentic problems, real consequences, and reflection on action.",
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      "tags": [
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      "title": "Vygotsky vs. Piaget",
      "body": "Vygotsky's social constructivism holds that higher mental functions first arise between people and only later become internal — learning is inherently social, unlike Piaget's focus on the individual's encounter with the physical world.",
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      "tags": [
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      "title": "The Original 1956 Taxonomy",
      "body": "Benjamin Bloom and colleagues at the University of Chicago published the original Taxonomy of Educational Objectives: Cognitive Domain in 1956, decades before the 2001 revision led by Anderson and Krathwohl.",
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        "creditUrl": "https://commons.wikimedia.org/wiki/File:Cyberdiversity-Improving-the-Informatic-Value-of-Diverse-Tropical-Arthropod-Inventories-pone.0115750.g002.jpg",
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      "tags": [
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      "title": "Bloom's Original Summit",
      "body": "In the 1956 taxonomy, Evaluation sat at the very top of the hierarchy, following Synthesis. The 2001 revision swapped the order, dropping Evaluate one rung below the new top level, Create.",
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      "id": "fi-lt-mcq-mastery-threshold",
      "tags": [
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      "title": "Instructional Gap, Not Deficit",
      "body": "In mastery learning, a student who doesn't reach the threshold is treated as evidence the instruction missed the mark, not as a personal deficit — the fix is to correct the teaching and re-test.",
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      "tags": [
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      "title": "Before Bloom: John Carroll",
      "body": "Mastery learning wasn't Bloom's original idea — John Carroll developed the model first, and Bloom later expanded it.",
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      "tags": [
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      "title": "Reinforcement's 1.2 Sigma",
      "body": "Among Bloom's ranked alterable variables, reinforcement placed second at 1.2 sigma — well behind one-to-one tutoring's top effect size of 2 sigma.",
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      "illustration": {
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      "title": "Two Ways to 1 Sigma",
      "body": "Two of Bloom's alterable variables each produced a 1-sigma effect: mastery learning built on feedback-corrective cycles, and simply increasing a student's time on task.",
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      "title": "Flow Is Autotelic",
      "body": "Flow theory calls an activity 'autotelic' when it's pursued purely because doing it is rewarding, with no outside payoff — like a student who keeps practicing piano long after the assignment is finished, simply because playing itself feels good.",
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      "tags": [
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      "title": "Flow's 2.3x Speedup",
      "body": "Research found that flow-optimized learning environments accelerate mastery by roughly 2.3 times compared to typical instruction — a substantial gain, though not an extraordinary one.",
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      "illustration": {
        "imageSearchTerm": "student absorbed focused learning",
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      "tags": [
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      "title": "Dual Coding's Origin",
      "body": "Allan Paivio proposed Dual Coding Theory in 1971 — distinct from Sweller's later Cognitive Load Theory (1988) and Gagné's earlier Conditions of Learning (1965).",
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      "tags": [
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      "title": "Verbal Plus Visual",
      "body": "Dual Coding Theory holds that humans operate with two interconnected memory systems: a verbal system for language, text, and narrative, and a visual system for imagery and spatial layout.",
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        "subject": "A teacher in a white shirt holding a flashcard with a large blue alligator-textured letter 'A' and the word 'ALLIGATOR' up to two young children seen from behind in a classroom",
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      "tags": [
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      "title": "Learning Outside the Mind",
      "body": "Connectivism's founders argued that behaviorism, cognitivism, and constructivism all locate learning inside the individual mind — missing the learning that happens in networks, organizations, and digital systems.",
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      "tags": [
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      "title": "Gagné's First Event",
      "body": "Gagné's Nine Events of Instruction open by gaining the learner's attention, before informing them of objectives — the sequence ends by building retention and transfer.",
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      "tags": [
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      "title": "Connectivism's Two Founders",
      "body": "George Siemens and Stephen Downes developed connectivism, 'the learning theory for the digital age,' around 2004–05 — after Gagné's 1965 Conditions of Learning and Sweller's 1988 load theory.",
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      "title": "The Why of Learning",
      "body": "Universal Design for Learning organizes its three principles around what (Representation), how (Action & Expression), and why (Engagement) — the why being learner motivation and interest.",
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      "tags": [
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      "title": "Loci and Spatial Memory",
      "body": "The method of loci works by exploiting the brain's strong spatial-episodic memory — placing facts along a familiar mental route, which is how memory champions manage to memorize thousands of digits.",
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        "subject": "A grand white Baroque gallery with ornate stucco ceiling, repeated pilastered bays and oval windows down both sides, a checkerboard marble floor, converging to a small doorway at the far end; empty of people and text.",
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      "tags": [
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      "title": "The Keyword Method",
      "body": "The Keyword Method is a language-learning mnemonic that links a foreign word's sound to a bridging image — for example, picturing a four (quatre) on a fork to remember the French word fourchette.",
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      "title": "An Ancient Memory Trick",
      "body": "The method of loci, or memory palace, originated in ancient Greece and Rome, where orators used it to hold long speeches in sequence — long before its Renaissance revival.",
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      "tags": [
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      "title": "Evaluate Never Stops",
      "body": "ADDIE's Evaluate phase isn't a final gate — it runs continuously through Analyze, Design, Develop, and Implement, surfacing problems early instead of waiting until after delivery.",
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      "title": "ADDIE Starts With Analyze",
      "body": "ADDIE's front-end Analyze phase is where a team identifies goals, audience, prior knowledge, and constraints — before Design sets objectives, assessment, and sequencing.",
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      "title": "ADDIE's Build Phase",
      "body": "In ADDIE's Develop phase, a team produces the actual videos, activities, and quiz items planned during Design — turning objectives and sequencing into finished material.",
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      "id": "fi-lt-mcq-backward-design",
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      "title": "Start From the End",
      "body": "Understanding by Design (Wiggins & McTighe, 1998) is the framework built on 'backward design' — starting from the outcomes learners should achieve and working back from there.",
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      "tags": [
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      "title": "ADDIE's Agile Answer",
      "body": "SAM — Michael Allen's Successive Approximation Model (2012) — is the iterative counterpoint to ADDIE, built on rapid, agile prototyping and short revision cycles.",
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      "tags": [
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      "title": "Merrill's First Principles",
      "body": "Merrill's Principles of Instruction (2002) offer task-centered 'first principles' of design — problem-centered, activation, demonstration, application, and integration — rather than a systems view of instruction.",
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      "tags": [
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      "title": "Nine Parts, Not Phases",
      "body": "The Dick & Carey Model (1978) treats instruction as nine interacting components rather than a set of sequential phases, making it a more prescriptive systems view than ADDIE.",
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      "id": "fi-ot-personalization-1",
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      "title": "What a Tutor Must Know",
      "body": "Khan argues an effective tutor must understand four things about a learner: where they are, what they know, how they learn, and what engages them.",
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      "tags": [
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      "title": "Personalization's Price Tag",
      "body": "Historically, the kind of individual attention a great tutor provides was only available through expensive private tutoring — affordable for wealthy families but out of reach for most students.",
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      "title": "Built on GPT-4",
      "body": "Khanmigo was built on GPT-4 in partnership with OpenAI, serving as Khan Academy's proof of concept for the book's thesis.",
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      "title": "Research Assistants category",
      "body": "Google NotebookLM ingests documents to build a research-grounded knowledge base, placing it in the Research Assistants category alongside Perplexity.",
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      "body": "MagicSchool and Diffit lead the Teacher Tools category, which keeps the human educator central by handling lesson planning, rubric generation, and administrative reduction.",
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      "title": "AI Tutors category",
      "body": "AI Tutors is the category defined as adaptive, conversational one-to-one instruction — the closest digital analog to a personal teacher.",
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      "title": "Intelligent tutoring's dual model",
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      "title": "EdTech investment hits $2.6B",
      "body": "Global EdTech investment reached $2.6 billion in 2025, up roughly 11% over 2024, with capital concentrating in AI-enabled and workforce-aligned products.",
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      "title": "2025's two headline deals",
      "body": "The year's two biggest EdTech deals were Workday's $1.1 billion acquisition of Sana and Coursera's $2.5 billion all-stock acquisition of Udemy.",
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      "title": "Canvas overtakes Blackboard",
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      "title": "PLATO's 1960 debut",
      "body": "Donald Bitzer launched PLATO at the University of Illinois in 1960 — a mainframe system with simultaneous users and touchscreens, anticipating modern e-learning by thirty years.",
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      "title": "LMS history, in sequence",
      "body": "The LMS timeline runs Pressey's machine (1924), then PLATO (1960), then SCORM (2001), then Moodle (2002) — SCORM arrives decades after PLATO, not before it.",
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      "title": "Canvas's maker: Instructure",
      "body": "Canvas is built by Instructure — not to be confused with Blackboard Inc., which makes the rival product, or Moodle, which came from Martin Dougiamas.",
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      "title": "Failure as feedback",
      "body": "Mastery framing is the core game mechanic that reframes failure as information rather than judgment — treating a wrong answer as feedback, not a verdict on the learner.",
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      "title": "What gamification really means",
      "body": "Gamification means applying game design elements — points, badges, leaderboards, levels, narrative — to non-game contexts to boost engagement, not building actual games.",
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      "id": "fi-ot-sdt-2",
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      "title": "SDT's three core needs",
      "body": "Self-Determination Theory names autonomy, competence, and relatedness as its three basic psychological needs — not points and badges, which are surface mechanics, not needs.",
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        "subject": "Four diverse adults meeting hands in a group high-five outdoors against dense green foliage, all smiling; no text or logos in frame",
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      "tags": [
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      "title": "The overjustification effect",
      "body": "Adding prize money to a hobby someone already loves can backfire — the overjustification effect describes how external rewards for an already-intrinsically-motivating task can undermine that intrinsic motivation.",
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        "credit": "Wikimedia Commons · see source",
        "creditUrl": "https://commons.wikimedia.org/wiki/File:Aurelio_Voltaire_Wave-Gotik-Treffen_2016_01.jpg",
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      "prompt": {
        "modality": "text",
        "value": "Per the testing effect, how often should low-stakes quizzes be given?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Only once, right before the final"
        },
        {
          "modality": "text",
          "value": "Frequently — the testing itself drives learning"
        },
        {
          "modality": "text",
          "value": "Rarely, so quizzes stay high-stakes"
        },
        {
          "modality": "text",
          "value": "Never; re-reading works just as well"
        }
      ],
      "correctIndex": 1,
      "explanation": "MIT Open Learning's practical implication: frequent low-stakes quizzing works because being tested is itself the learning event, not just an assessment.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "79pdup17jykfv"
    },
    {
      "id": "ot-cov-obj-retrieval-practice-2",
      "shape": "mcq",
      "tags": [
        "retrieval-practice",
        "testing-effect",
        "quizzing"
      ],
      "prompt": {
        "modality": "text",
        "value": "Why does frequent testing (not just re-reading) drive learning gains, per the testing effect?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Frequent testing eliminates need for spaced repetition"
        },
        {
          "modality": "text",
          "value": "Quizzes mainly motivate through fear of failure"
        },
        {
          "modality": "text",
          "value": "Being tested is itself the learning event"
        },
        {
          "modality": "text",
          "value": "Testing only works when high-stakes and graded"
        }
      ],
      "correctIndex": 2,
      "explanation": "MIT's practical implication: frequent low-stakes quizzing works because the act of being tested is itself the learning event, not merely an assessment of prior learning.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "orwc6115euhg3"
    },
    {
      "id": "ot-cov-obj-verb-ladder-1",
      "shape": "mcq",
      "tags": [
        "blooms-taxonomy",
        "verb-ladder",
        "create"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which level was moved to the summit of the revised Bloom's Taxonomy?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Analyze"
        },
        {
          "modality": "text",
          "value": "Evaluate"
        },
        {
          "modality": "text",
          "value": "Create"
        },
        {
          "modality": "text",
          "value": "Understand"
        }
      ],
      "correctIndex": 2,
      "explanation": "The 2001 revision swapped the top two levels, moving Create above Evaluate to the summit of the hierarchy.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "160raaz1boqfxd"
    },
    {
      "id": "ot-cov-obj-verb-ladder-2",
      "shape": "mcq",
      "tags": [
        "blooms-taxonomy",
        "verb-ladder",
        "create"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which verb-level ranks highest in the 2001 Bloom's revision, above Evaluate?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Analyze"
        },
        {
          "modality": "text",
          "value": "Apply"
        },
        {
          "modality": "text",
          "value": "Create"
        },
        {
          "modality": "text",
          "value": "Remember"
        }
      ],
      "correctIndex": 2,
      "explanation": "Synthesis (1956) became Create (2001) and took the top spot, ranking above Evaluate in the revised hierarchy.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1lsda2q4hqtc6"
    },
    {
      "id": "ot-cov-obj-alterable-variables-1",
      "shape": "mcq",
      "tags": [
        "two-sigma",
        "effect-size",
        "alterable-variables"
      ],
      "prompt": {
        "modality": "text",
        "value": "Among Bloom's alterable instructional variables, which tops the ranking by effect size?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Mastery learning, feedback-corrective"
        },
        {
          "modality": "text",
          "value": "Reinforcement"
        },
        {
          "modality": "text",
          "value": "Cooperative learning"
        },
        {
          "modality": "text",
          "value": "One-to-one tutorial instruction"
        }
      ],
      "correctIndex": 3,
      "explanation": "One-to-one tutorial instruction topped Bloom's ranking of alterable variables at 2 sigma, the largest effect size measured.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "6wfwdf1qwiwvl"
    },
    {
      "id": "ot-cov-obj-alterable-variables-2",
      "shape": "mcq",
      "tags": [
        "two-sigma",
        "effect-size",
        "alterable-variables"
      ],
      "prompt": {
        "modality": "text",
        "value": "What effect size did one-to-one tutorial instruction reach in Bloom's ranking?"
      },
      "options": [
        {
          "modality": "text",
          "value": "0.6 sigma"
        },
        {
          "modality": "text",
          "value": "2 sigma"
        },
        {
          "modality": "text",
          "value": "1.2 sigma"
        },
        {
          "modality": "text",
          "value": "1 sigma"
        }
      ],
      "correctIndex": 1,
      "explanation": "Bloom's alterable-variables ranking put one-to-one tutorial instruction at 2 sigma — the top of the list.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "iay49m1l5617q"
    },
    {
      "id": "ot-cov-obj-alterable-variables-3",
      "shape": "mcq",
      "tags": [
        "two-sigma",
        "effect-size",
        "alterable-variables"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which alterable variable sits at the bottom of Bloom's effect-size ranking?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Student time on task"
        },
        {
          "modality": "text",
          "value": "Cooperative learning"
        },
        {
          "modality": "text",
          "value": "Graded homework"
        },
        {
          "modality": "text",
          "value": "Classroom morale"
        }
      ],
      "correctIndex": 3,
      "explanation": "Classroom morale contributed the smallest effect, 0.6 sigma, placing it at the bottom of Bloom's ranking of alterable variables.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "te2qfaapc08a"
    },
    {
      "id": "ot-cov-obj-alterable-variables-4",
      "shape": "mcq",
      "tags": [
        "two-sigma",
        "effect-size",
        "alterable-variables"
      ],
      "prompt": {
        "modality": "text",
        "value": "What effect size does classroom morale contribute, per Bloom's ranking?"
      },
      "options": [
        {
          "modality": "text",
          "value": "0.8 sigma"
        },
        {
          "modality": "text",
          "value": "2 sigma"
        },
        {
          "modality": "text",
          "value": "0.6 sigma"
        },
        {
          "modality": "text",
          "value": "1.2 sigma"
        }
      ],
      "correctIndex": 2,
      "explanation": "Classroom morale reached only 0.6 sigma — the smallest effect size in Bloom's ranking of alterable instructional variables.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1affe8u7vbt3e"
    },
    {
      "id": "ot-cov-obj-flow-1",
      "shape": "mcq",
      "tags": [
        "flow",
        "challenge-skill-balance",
        "boredom"
      ],
      "prompt": {
        "modality": "text",
        "value": "In flow theory, what results when a task's challenge falls far below the learner's skill?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Anxiety"
        },
        {
          "modality": "text",
          "value": "Boredom"
        },
        {
          "modality": "text",
          "value": "Burnout"
        },
        {
          "modality": "text",
          "value": "Autotelic engagement"
        }
      ],
      "correctIndex": 1,
      "explanation": "When challenge is far below skill, engagement collapses into boredom — the mirror-image failure mode to anxiety, which occurs when challenge exceeds skill.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1wayhi1nkzesr"
    },
    {
      "id": "ot-cov-obj-flow-2",
      "shape": "mcq",
      "tags": [
        "flow",
        "challenge-skill-balance",
        "boredom"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which state does Csikszentmihalyi's flow theory link to a task that is too easy?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Boredom"
        },
        {
          "modality": "text",
          "value": "Cognitive load"
        },
        {
          "modality": "text",
          "value": "Anxiety"
        },
        {
          "modality": "text",
          "value": "Autotelic reward"
        }
      ],
      "correctIndex": 0,
      "explanation": "Flow theory holds that a task far easier than the learner's skill produces boredom, while one far harder produces anxiety.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1dawy8jval54"
    },
    {
      "id": "ot-cov-obj-connectivism-gagne-1",
      "shape": "mcq",
      "tags": [
        "connectivism",
        "know-where",
        "digital-age-learning"
      ],
      "prompt": {
        "modality": "text",
        "value": "Per connectivism, what matters most in the AI era compared to memorized facts?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Avoiding AI tools during study"
        },
        {
          "modality": "text",
          "value": "Relying solely on classroom instruction"
        },
        {
          "modality": "text",
          "value": "Memorizing more facts than before"
        },
        {
          "modality": "text",
          "value": "Knowing where to find and evaluate information"
        }
      ],
      "correctIndex": 3,
      "explanation": "Connectivism's core claim is that knowing where to find information — the 'know-where' — outweighs knowing the facts themselves, especially now that AI can answer instantly.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "16gul91c4h9g7"
    },
    {
      "id": "ot-cov-obj-connectivism-gagne-2",
      "shape": "mcq",
      "tags": [
        "connectivism",
        "learning-gap",
        "networks"
      ],
      "prompt": {
        "modality": "text",
        "value": "What gap did Siemens and Downes say older learning theories missed?"
      },
      "options": [
        {
          "modality": "text",
          "value": "The difference between short- and long-term memory"
        },
        {
          "modality": "text",
          "value": "The role of feedback in classroom instruction"
        },
        {
          "modality": "text",
          "value": "Learning that happens outside the mind, across networks"
        },
        {
          "modality": "text",
          "value": "How motivation affects retention"
        }
      ],
      "correctIndex": 2,
      "explanation": "Connectivism argued behaviorism, cognitivism, and constructivism only accounted for learning inside an individual mind, missing learning distributed across networks and systems.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "4cbmnm13p09o6"
    },
    {
      "id": "ot-cov-obj-connectivism-gagne-3",
      "shape": "mcq",
      "tags": [
        "gagne",
        "learning-outcomes",
        "instructional-design"
      ],
      "prompt": {
        "modality": "text",
        "value": "Gagné's Conditions of Learning named five outcome categories. Which is one?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Mastery learning"
        },
        {
          "modality": "text",
          "value": "Autotelic engagement"
        },
        {
          "modality": "text",
          "value": "Dual coding"
        },
        {
          "modality": "text",
          "value": "Motor skills"
        }
      ],
      "correctIndex": 3,
      "explanation": "Gagné's five learning-outcome categories are verbal information, intellectual skills, cognitive strategies, motor skills, and attitudes.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "ai9zs5g0s8hr"
    },
    {
      "id": "ot-cov-obj-connectivism-gagne-4",
      "shape": "mcq",
      "tags": [
        "gagne",
        "nine-events",
        "instructional-design"
      ],
      "prompt": {
        "modality": "text",
        "value": "What is the very first step in Gagné's Nine Events of Instruction?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Provide learning guidance"
        },
        {
          "modality": "text",
          "value": "Enhance retention and transfer"
        },
        {
          "modality": "text",
          "value": "Gain attention"
        },
        {
          "modality": "text",
          "value": "Assess performance"
        }
      ],
      "correctIndex": 2,
      "explanation": "Gagné's sequence opens by gaining attention, since information that goes unattended is never encoded in the first place.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1bukshsy50560"
    },
    {
      "id": "ot-cov-obj-udl-mnemonics-1",
      "shape": "mcq",
      "tags": [
        "mnemonics",
        "keyword-method",
        "dual-coding"
      ],
      "prompt": {
        "modality": "text",
        "value": "The Keyword Method links a foreign word's sound to which of these to aid recall?"
      },
      "options": [
        {
          "modality": "text",
          "value": "A spatial route through a familiar building"
        },
        {
          "modality": "text",
          "value": "A rote repetition drill"
        },
        {
          "modality": "text",
          "value": "A grammar conjugation pattern"
        },
        {
          "modality": "text",
          "value": "A vivid image that bridges to the translation"
        }
      ],
      "correctIndex": 3,
      "explanation": "The Keyword Method links a foreign word's sound to a memorable image that then bridges to its translation — a different mechanism than the Method of Loci's spatial route.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "g4g5e0136w60g"
    },
    {
      "id": "ot-cov-obj-udl-mnemonics-2",
      "shape": "mcq",
      "tags": [
        "mnemonics",
        "keyword-method",
        "dual-coding"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which example illustrates the Keyword Method for learning a French word?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Walking a familiar route to recall items in order"
        },
        {
          "modality": "text",
          "value": "Picturing a four on a fork to remember \"fourchette\""
        },
        {
          "modality": "text",
          "value": "Repeating the word aloud ten times"
        },
        {
          "modality": "text",
          "value": "Pairing a diagram with a spoken explanation"
        }
      ],
      "correctIndex": 1,
      "explanation": "The guide's Keyword Method example links the sound of \"fourchette\" (fork) to a picture of a four (quatre) on a fork, bridging sound to translation via imagery.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1khmembulym49"
    },
    {
      "id": "ot-cov-obj-scifi-inspirations-1",
      "shape": "mcq",
      "tags": [
        "brave-new-words",
        "khan",
        "sci-fi-inspirations"
      ],
      "prompt": {
        "modality": "text",
        "value": "Which work is explicitly named as NOT one of Khan's three sci-fi inspirations in Brave New Words' opening?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Snow Crash"
        },
        {
          "modality": "text",
          "value": "The Diamond Age"
        },
        {
          "modality": "text",
          "value": "Ender's Game"
        },
        {
          "modality": "text",
          "value": "\"The Fun They Had\""
        }
      ],
      "correctIndex": 0,
      "explanation": "The guide states Snow Crash does not appear as an inspiration, while The Diamond Age, Ender's Game, and \"The Fun They Had\" are Khan's three cited works.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "lt7bwe1g8ooq"
    },
    {
      "id": "ot-cov-obj-platforms-1",
      "shape": "mcq",
      "tags": [
        "duolingo",
        "birdbrain",
        "adaptive-learning"
      ],
      "prompt": {
        "modality": "text",
        "value": "What is the name of Duolingo's proprietary adaptive learning model?"
      },
      "options": [
        {
          "modality": "text",
          "value": "LearnLM"
        },
        {
          "modality": "text",
          "value": "Max"
        },
        {
          "modality": "text",
          "value": "BirdBrain"
        },
        {
          "modality": "text",
          "value": "Lily"
        }
      ],
      "correctIndex": 2,
      "explanation": "BirdBrain is Duolingo's proprietary adaptive model; Max is the GPT-4 tier built on top of it, and Lily is a chat mode within Max.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1c5k9m41e0jwos"
    },
    {
      "id": "ot-cov-obj-platforms-2",
      "shape": "mcq",
      "tags": [
        "duolingo",
        "birdbrain",
        "adaptive-learning"
      ],
      "prompt": {
        "modality": "text",
        "value": "What does Duolingo's BirdBrain system primarily do?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Adjusts content, sequence, and difficulty in real time"
        },
        {
          "modality": "text",
          "value": "Generates audio podcasts from documents"
        },
        {
          "modality": "text",
          "value": "Grades essays against a rubric"
        },
        {
          "modality": "text",
          "value": "Provides roleplay scenarios via GPT-4"
        }
      ],
      "correctIndex": 0,
      "explanation": "BirdBrain is an adaptive system that adjusts content, sequence, and difficulty in real time based on learner performance history.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "mbqh35gq927n"
    },
    {
      "id": "ot-cov-obj-platforms-3",
      "shape": "mcq",
      "tags": [
        "synthesis",
        "edtech",
        "spacex"
      ],
      "prompt": {
        "modality": "text",
        "value": "Synthesis, the K-6 math platform, was originally built for which organization's employee school?"
      },
      "options": [
        {
          "modality": "text",
          "value": "SpaceX"
        },
        {
          "modality": "text",
          "value": "OpenAI"
        },
        {
          "modality": "text",
          "value": "Google"
        },
        {
          "modality": "text",
          "value": "Khan Academy"
        }
      ],
      "correctIndex": 0,
      "explanation": "Synthesis was built for the SpaceX employee school, which the guide says explains its design focus on problem-solving over test prep.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "yxk7vlixncr"
    },
    {
      "id": "ot-cov-obj-platforms-4",
      "shape": "mcq",
      "tags": [
        "synthesis",
        "edtech",
        "spacex"
      ],
      "prompt": {
        "modality": "text",
        "value": "Who founded Synthesis, the K-6 math platform?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Chrisman Frank"
        },
        {
          "modality": "text",
          "value": "Nick Pelling"
        },
        {
          "modality": "text",
          "value": "Martin Dougiamas"
        },
        {
          "modality": "text",
          "value": "Salman Khan"
        }
      ],
      "correctIndex": 0,
      "explanation": "Synthesis was founded by Chrisman Frank, built originally for the SpaceX employee school.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "vv1haf1oqwhbx"
    },
    {
      "id": "ot-cov-obj-market-1",
      "shape": "mcq",
      "tags": [
        "edtech-market",
        "investment",
        "market-size"
      ],
      "prompt": {
        "modality": "text",
        "value": "What was global EdTech investment in 2025?"
      },
      "options": [
        {
          "modality": "text",
          "value": "$2.6 billion"
        },
        {
          "modality": "text",
          "value": "$10 million"
        },
        {
          "modality": "text",
          "value": "$5.47 billion"
        },
        {
          "modality": "text",
          "value": "$1.72 billion"
        }
      ],
      "correctIndex": 0,
      "explanation": "Global EdTech investment hit $2.6 billion in 2025 — distinct from the $1.72B/$5.47B adaptive-learning market-size figures.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "5uetbupcb0ry"
    },
    {
      "id": "ot-cov-obj-market-2",
      "shape": "mcq",
      "tags": [
        "edtech-market",
        "investment",
        "market-size"
      ],
      "prompt": {
        "modality": "text",
        "value": "By roughly how much did global EdTech investment grow in 2025 versus 2024?"
      },
      "options": [
        {
          "modality": "text",
          "value": "50%"
        },
        {
          "modality": "text",
          "value": "30%"
        },
        {
          "modality": "text",
          "value": "11%"
        },
        {
          "modality": "text",
          "value": "25%"
        }
      ],
      "correctIndex": 2,
      "explanation": "Global EdTech investment rose roughly 11% over 2024, distinct from the 30-50% learning-time and 15-25% outcome figures cited elsewhere in the lesson.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "pp4d0ekukvbm"
    },
    {
      "id": "ot-cov-obj-interop-standards-1",
      "shape": "mcq",
      "tags": [
        "xapi",
        "actor-verb-object",
        "interoperability"
      ],
      "prompt": {
        "modality": "text",
        "value": "What three-part structure does xAPI use to record learning experiences?"
      },
      "options": [
        {
          "modality": "text",
          "value": "User-Event-Timestamp"
        },
        {
          "modality": "text",
          "value": "Subject-Predicate-Grade"
        },
        {
          "modality": "text",
          "value": "Learner-Verb-Score"
        },
        {
          "modality": "text",
          "value": "Actor-Verb-Object"
        }
      ],
      "correctIndex": 3,
      "explanation": "xAPI captures experiences as Actor-Verb-Object statements, e.g. 'Jane completed the quiz' — far richer than SCORM's completions-only tracking.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "1oa132t1pfbgnj"
    },
    {
      "id": "ot-cov-obj-interop-standards-2",
      "shape": "mcq",
      "tags": [
        "xapi",
        "actor-verb-object",
        "interoperability"
      ],
      "prompt": {
        "modality": "text",
        "value": "In the xAPI statement \"Maria completed the simulation,\" what role does \"completed\" play?"
      },
      "options": [
        {
          "modality": "text",
          "value": "Actor"
        },
        {
          "modality": "text",
          "value": "Object"
        },
        {
          "modality": "text",
          "value": "Verb"
        },
        {
          "modality": "text",
          "value": "Result"
        }
      ],
      "correctIndex": 2,
      "explanation": "In xAPI's Actor-Verb-Object form, 'Maria' is the Actor, 'the simulation' is the Object, and 'completed' is the Verb.",
      "source": {
        "label": "Education Theory & Learning Technology — Objective Test"
      },
      "uid": "170hkd2a2rl16"
    }
  ],
  "lessons": [
    {
      "id": "l1-how-we-learn",
      "title": "How Humans Learn",
      "order": 1,
      "studyGuidePath": "/packs/learning-theory/guides/l1-p1-three-modes.md",
      "sources": [
        {
          "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
        }
      ],
      "parts": [
        {
          "id": "l1-p1-three-modes",
          "title": "Three modes of learning",
          "order": 1,
          "blurb": "Hebbian wiring, the exposure-retrieval-application loop, and passive vs. active vs. interactive.",
          "studyGuideAnchor": "three-modes-of-learning",
          "itemIds": [
            "lt-fact-hebbian",
            "lt-def-hebbian",
            "lt-fact-three-stages",
            "lt-pair-passive",
            "lt-pair-active",
            "lt-pair-interactive",
            "lt-mcq-deepest-mode",
            "lt-cmp-passive-active",
            "czr-learning-theory-lt-def-hebbian",
            "tf-df-learning-theory-lt-def-hebbian",
            "concept-rw-learning-theory-passive-learning",
            "concept-rw-learning-theory-active-learning",
            "concept-rw-learning-theory-interactive-learning",
            "concept-rw-learning-theory-hebbian-learning",
            "ot-hebbian-1",
            "ot-hebbian-2",
            "ot-hebbian-3",
            "ot-hebbian-4",
            "ot-hebbian-5",
            "ot-modes-1",
            "ot-modes-2",
            "ot-modes-3",
            "ot-modes-4",
            "fi-ot-modes-2",
            "fi-ot-hebbian-2",
            "fi-ot-hebbian-5"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l1-p1-three-modes.md"
        },
        {
          "id": "l1-p2-forgetting-spacing",
          "title": "The forgetting curve & spaced repetition",
          "order": 2,
          "blurb": "Ebbinghaus's decay, the numbers behind it, and the spacing countermeasure that beats cramming.",
          "studyGuideAnchor": "the-forgetting-curve-spaced-repetition",
          "itemIds": [
            "lt-fact-forgetting-curve",
            "lt-def-forgetting-curve",
            "lt-num-forget-30min",
            "lt-num-forget-24hr",
            "lt-def-spaced-repetition",
            "lt-def-srs",
            "lt-pair-anki",
            "lt-proc-spacing-schedule",
            "mcq-rw-l1-p2-forgetting-spacing",
            "czr-learning-theory-lt-def-forgetting-curve",
            "czr-learning-theory-lt-def-spaced-repetition",
            "czr-learning-theory-lt-def-srs",
            "cz-learning-theory-lt-fact-forgetting-curve",
            "tf-t-learning-theory-lt-pair-anki",
            "tf-df-learning-theory-lt-def-forgetting-curve",
            "tf-d-learning-theory-lt-def-spaced-repetition",
            "tf-d-learning-theory-lt-def-srs",
            "ot-forget-1",
            "ot-forget-2",
            "ot-forget-3",
            "ot-forget-4",
            "ot-spacing-1",
            "ot-spacing-2",
            "ot-spacing-3",
            "ot-spacing-4",
            "ot-spacing-5",
            "fi-ot-forget-1",
            "fi-ot-forget-2",
            "fi-mcq-rw-l1-p2-forgetting-spacing",
            "fi-ot-spacing-2"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l1-p2-forgetting-spacing.md"
        },
        {
          "id": "l1-p3-retrieval",
          "title": "Retrieval practice (the testing effect)",
          "order": 3,
          "blurb": "Why pulling information out beats putting it back in — and what the research says.",
          "studyGuideAnchor": "retrieval-practice-the-testing-effect",
          "itemIds": [
            "lt-fact-testing-effect",
            "lt-def-retrieval-practice",
            "lt-pair-roediger-butler",
            "lt-pair-karpicke-roediger",
            "lt-mcq-mit-implication",
            "czr-learning-theory-lt-def-retrieval-practice",
            "tf-f-learning-theory-lt-pair-roediger-butler",
            "tf-d-learning-theory-lt-def-retrieval-practice",
            "ot-retrieval-1",
            "ot-retrieval-2",
            "ot-retrieval-3",
            "ot-retrieval-4",
            "fi-lt-mcq-mit-implication",
            "fi-ot-retrieval-2",
            "fi-ot-retrieval-3",
            "fi-ot-retrieval-4",
            "ot-cov-obj-retrieval-practice-1",
            "ot-cov-obj-retrieval-practice-2"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l1-p3-retrieval.md"
        }
      ],
      "objectives": [
        {
          "id": "obj-hebbian-mechanism",
          "statement": "Explain Hebbian learning: how repeated co-activation strengthens synaptic connections",
          "demonstrationIds": [
            "d-hebbian"
          ]
        },
        {
          "id": "obj-three-modes",
          "statement": "Distinguish passive, active, and interactive learning, and identify which mode forces the deepest retrieval and schema negotiation.",
          "demonstrationIds": [
            "d-modes",
            "d-mode-concepts"
          ]
        },
        {
          "id": "obj-forgetting-curve",
          "statement": "Describe Ebbinghaus's forgetting curve and quantify how much unreviewed information is lost within 30 minutes and 24 hours.",
          "demonstrationIds": [
            "d-forgetting-def",
            "d-forgetting-numbers"
          ]
        },
        {
          "id": "obj-spaced-repetition",
          "statement": "Explain spaced repetition over expanding intervals and how SRS tools like Anki schedule reviews at the optimal moment.",
          "demonstrationIds": [
            "d-spacing",
            "d-srs"
          ]
        },
        {
          "id": "obj-retrieval-practice",
          "statement": "Explain retrieval practice (the testing effect), cite its key studies, and state the practical implication for frequent low-stakes quizzing.",
          "demonstrationIds": [
            "d-retrieval",
            "d-retrieval-evidence"
          ]
        }
      ],
      "demonstrations": [
        {
          "id": "d-hebbian",
          "label": "Hebbian learning",
          "itemIds": [
            "lt-def-hebbian",
            "czr-learning-theory-lt-def-hebbian",
            "concept-rw-learning-theory-hebbian-learning"
          ]
        },
        {
          "id": "d-modes",
          "label": "Three modes ranked",
          "itemIds": [
            "lt-pair-passive",
            "lt-pair-active",
            "lt-pair-interactive",
            "lt-mcq-deepest-mode"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-mode-concepts",
          "label": "Mode concepts",
          "itemIds": [
            "concept-rw-learning-theory-passive-learning",
            "concept-rw-learning-theory-active-learning",
            "concept-rw-learning-theory-interactive-learning"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-forgetting-def",
          "label": "Forgetting curve",
          "itemIds": [
            "lt-def-forgetting-curve",
            "cz-learning-theory-lt-fact-forgetting-curve",
            "czr-learning-theory-lt-def-forgetting-curve"
          ]
        },
        {
          "id": "d-forgetting-numbers",
          "label": "Decay figures",
          "itemIds": [
            "lt-num-forget-30min",
            "lt-num-forget-24hr",
            "mcq-rw-l1-p2-forgetting-spacing"
          ]
        },
        {
          "id": "d-spacing",
          "label": "Spaced repetition",
          "itemIds": [
            "lt-def-spaced-repetition",
            "czr-learning-theory-lt-def-spaced-repetition",
            "tf-d-learning-theory-lt-def-spaced-repetition"
          ]
        },
        {
          "id": "d-srs",
          "label": "SRS tools",
          "itemIds": [
            "lt-def-srs",
            "lt-pair-anki",
            "czr-learning-theory-lt-def-srs",
            "tf-t-learning-theory-lt-pair-anki"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-retrieval",
          "label": "Retrieval practice",
          "itemIds": [
            "lt-def-retrieval-practice",
            "czr-learning-theory-lt-def-retrieval-practice",
            "tf-d-learning-theory-lt-def-retrieval-practice",
            "ot-cov-obj-retrieval-practice-1",
            "ot-cov-obj-retrieval-practice-2"
          ]
        },
        {
          "id": "d-retrieval-evidence",
          "label": "Testing-effect evidence",
          "itemIds": [
            "lt-pair-karpicke-roediger",
            "lt-pair-roediger-butler",
            "lt-mcq-mit-implication"
          ],
          "requiredCorrect": 2
        }
      ],
      "objectiveTests": [
        {
          "id": "test-hebbian-mechanism",
          "objectiveId": "obj-hebbian-mechanism",
          "title": "Hebbian Learning",
          "mcqIds": [
            "ot-hebbian-1",
            "ot-hebbian-2",
            "ot-hebbian-3",
            "ot-hebbian-4",
            "ot-hebbian-5"
          ]
        },
        {
          "id": "test-three-modes",
          "objectiveId": "obj-three-modes",
          "title": "Three Modes of Learning",
          "mcqIds": [
            "lt-mcq-deepest-mode",
            "ot-modes-1",
            "ot-modes-2",
            "ot-modes-3",
            "ot-modes-4"
          ]
        },
        {
          "id": "test-forgetting-curve",
          "objectiveId": "obj-forgetting-curve",
          "title": "The Forgetting Curve",
          "mcqIds": [
            "mcq-rw-l1-p2-forgetting-spacing",
            "ot-forget-1",
            "ot-forget-2",
            "ot-forget-3",
            "ot-forget-4"
          ]
        },
        {
          "id": "test-spaced-repetition",
          "objectiveId": "obj-spaced-repetition",
          "title": "Spaced Repetition & SRS",
          "mcqIds": [
            "ot-spacing-1",
            "ot-spacing-2",
            "ot-spacing-3",
            "ot-spacing-4",
            "ot-spacing-5"
          ]
        },
        {
          "id": "test-retrieval-practice",
          "objectiveId": "obj-retrieval-practice",
          "title": "Retrieval & the Testing Effect",
          "mcqIds": [
            "lt-mcq-mit-implication",
            "ot-retrieval-1",
            "ot-retrieval-2",
            "ot-retrieval-3",
            "ot-retrieval-4",
            "ot-cov-obj-retrieval-practice-1",
            "ot-cov-obj-retrieval-practice-2"
          ]
        }
      ]
    },
    {
      "id": "l2-learning-theories",
      "title": "Learning Theories: Behaviorism to Constructivism",
      "order": 2,
      "studyGuidePath": "/packs/learning-theory/guides/l2-p1-behaviorism.md",
      "sources": [
        {
          "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
        }
      ],
      "parts": [
        {
          "id": "l2-p1-behaviorism",
          "title": "Behaviorism",
          "order": 1,
          "blurb": "Skinner, Pavlov, and Watson: learning as observable behavior shaped by reinforcement — and why it still runs your streak counter.",
          "studyGuideAnchor": "behaviorism",
          "itemIds": [
            "lt-fact-behaviorism-intro",
            "lt-def-operant-conditioning",
            "lt-pair-skinner",
            "lt-pair-pavlov",
            "lt-pair-watson",
            "lt-fact-behaviorism-today",
            "lt-fact-behaviorism-terms",
            "mcq-rw-l2-p1-behaviorism",
            "czr-learning-theory-lt-def-operant-conditioning",
            "tf-f-learning-theory-lt-pair-skinner",
            "tf-f-learning-theory-lt-pair-pavlov",
            "tf-f-learning-theory-lt-pair-watson",
            "tf-df-learning-theory-lt-def-operant-conditioning",
            "ot-behaviorism-founders-1",
            "ot-behaviorism-founders-2",
            "ot-behaviorism-founders-3",
            "ot-behaviorism-founders-4",
            "ot-behaviorism-founders-5",
            "ot-operant-shaping-1",
            "ot-operant-shaping-2",
            "ot-operant-shaping-3",
            "ot-operant-shaping-4",
            "fi-ot-behaviorism-founders-1",
            "fi-ot-behaviorism-founders-2"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l2-p1-behaviorism.md"
        },
        {
          "id": "l2-p2-cognitivism",
          "title": "Cognitivism",
          "order": 2,
          "blurb": "Piaget, Bruner, Bandura, and Miller put the mind back in: schemas, assimilation, accommodation, equilibration, and chunking.",
          "studyGuideAnchor": "cognitivism",
          "itemIds": [
            "lt-fact-cognitivism-intro",
            "lt-def-schema",
            "lt-def-assimilation",
            "lt-def-accommodation",
            "lt-def-equilibration",
            "lt-def-chunking",
            "lt-cmp-assimilation-accommodation",
            "lt-pair-miller",
            "lt-proc-piaget-stages",
            "mcq-rw-l2-p2-cognitivism",
            "czr-learning-theory-lt-def-chunking",
            "czr-learning-theory-lt-def-schema",
            "czr-learning-theory-lt-def-assimilation",
            "czr-learning-theory-lt-def-accommodation",
            "czr-learning-theory-lt-def-equilibration",
            "tf-t-learning-theory-lt-pair-miller",
            "tf-df-learning-theory-lt-def-chunking",
            "tf-df-learning-theory-lt-def-schema",
            "tf-df-learning-theory-lt-def-assimilation",
            "tf-d-learning-theory-lt-def-accommodation",
            "tf-d-learning-theory-lt-def-equilibration",
            "concept-rw-learning-theory-schema",
            "concept-rw-learning-theory-assimilation",
            "concept-rw-learning-theory-accommodation",
            "concept-rw-learning-theory-equilibration",
            "ot-piaget-processes-1",
            "ot-piaget-processes-2",
            "ot-piaget-processes-3",
            "ot-piaget-processes-4",
            "ot-schema-chunking-1",
            "ot-schema-chunking-2",
            "ot-schema-chunking-3",
            "ot-schema-chunking-4",
            "ot-schema-chunking-5",
            "fi-ot-piaget-processes-1",
            "fi-ot-piaget-processes-2",
            "fi-ot-schema-chunking-2",
            "fi-ot-schema-chunking-3"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l2-p2-cognitivism.md"
        },
        {
          "id": "l2-p3-constructivism",
          "title": "Constructivism",
          "order": 3,
          "blurb": "Vygotsky's ZPD and the more knowledgeable other, scaffolding and fading, and Dewey's learn-by-doing.",
          "studyGuideAnchor": "constructivism",
          "itemIds": [
            "lt-fact-constructivism-intro",
            "lt-def-zpd",
            "lt-def-scaffolding",
            "lt-pair-vygotsky",
            "lt-pair-dewey",
            "lt-mcq-mko",
            "lt-fact-scaffolding-fading",
            "czr-learning-theory-lt-def-zpd",
            "czr-learning-theory-lt-def-scaffolding",
            "tf-f-learning-theory-lt-pair-dewey",
            "tf-d-learning-theory-lt-def-zpd",
            "tf-d-learning-theory-lt-def-scaffolding",
            "ot-constructivism-1",
            "ot-constructivism-2",
            "ot-constructivism-3",
            "ot-constructivism-4",
            "fi-lt-mcq-mko",
            "fi-ot-constructivism-3",
            "fi-ot-constructivism-4"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l2-p3-constructivism.md"
        }
      ],
      "objectives": [
        {
          "id": "obj-behaviorism-founders",
          "statement": "Identify behaviorism's founders (Skinner, Pavlov, Watson) and match each to their stimulus-response contribution.",
          "demonstrationIds": [
            "d-behaviorists",
            "d-behaviorist-tf"
          ]
        },
        {
          "id": "obj-operant-shaping",
          "statement": "Explain operant conditioning and how shaping reinforces successive approximations toward a target behavior.",
          "demonstrationIds": [
            "d-operant"
          ]
        },
        {
          "id": "obj-piaget-processes",
          "statement": "Distinguish assimilation, accommodation, and equilibration as Piaget's schema-change processes, and why mild surprise aids memory.",
          "demonstrationIds": [
            "d-piaget-defs",
            "d-piaget-why"
          ]
        },
        {
          "id": "obj-schema-chunking",
          "statement": "Define a schema and explain how chunking works within George Miller's 7±2 working-memory limit.",
          "demonstrationIds": [
            "d-schema",
            "d-chunking-miller"
          ]
        },
        {
          "id": "obj-constructivism",
          "statement": "Explain constructivism through the Zone of Proximal Development, scaffolding, and the roles of Vygotsky and Dewey.",
          "demonstrationIds": [
            "d-zpd-scaffolding",
            "d-constructivist-theorists"
          ]
        }
      ],
      "demonstrations": [
        {
          "id": "d-behaviorists",
          "label": "Behaviorist theorists",
          "itemIds": [
            "lt-pair-skinner",
            "lt-pair-pavlov",
            "lt-pair-watson"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-behaviorist-tf",
          "label": "Theorist attributions",
          "itemIds": [
            "tf-f-learning-theory-lt-pair-skinner",
            "tf-f-learning-theory-lt-pair-pavlov",
            "tf-f-learning-theory-lt-pair-watson"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-operant",
          "label": "Operant conditioning & shaping",
          "itemIds": [
            "lt-def-operant-conditioning",
            "czr-learning-theory-lt-def-operant-conditioning",
            "mcq-rw-l2-p1-behaviorism"
          ]
        },
        {
          "id": "d-piaget-defs",
          "label": "Schema-change processes",
          "itemIds": [
            "lt-def-assimilation",
            "lt-def-accommodation",
            "lt-def-equilibration"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-piaget-why",
          "label": "Equilibration effect",
          "itemIds": [
            "mcq-rw-l2-p2-cognitivism",
            "concept-rw-learning-theory-equilibration",
            "czr-learning-theory-lt-def-equilibration"
          ]
        },
        {
          "id": "d-schema",
          "label": "Schema",
          "itemIds": [
            "lt-def-schema",
            "czr-learning-theory-lt-def-schema",
            "concept-rw-learning-theory-schema"
          ]
        },
        {
          "id": "d-chunking-miller",
          "label": "Chunking & Miller",
          "itemIds": [
            "lt-def-chunking",
            "lt-pair-miller",
            "czr-learning-theory-lt-def-chunking",
            "tf-t-learning-theory-lt-pair-miller"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-zpd-scaffolding",
          "label": "ZPD & scaffolding",
          "itemIds": [
            "lt-def-zpd",
            "lt-def-scaffolding",
            "lt-mcq-mko"
          ]
        },
        {
          "id": "d-constructivist-theorists",
          "label": "Vygotsky & Dewey",
          "itemIds": [
            "lt-pair-vygotsky",
            "lt-pair-dewey",
            "tf-f-learning-theory-lt-pair-dewey"
          ]
        }
      ],
      "objectiveTests": [
        {
          "id": "test-behaviorism-founders",
          "objectiveId": "obj-behaviorism-founders",
          "title": "Behaviorism's Founders",
          "mcqIds": [
            "ot-behaviorism-founders-1",
            "ot-behaviorism-founders-2",
            "ot-behaviorism-founders-3",
            "ot-behaviorism-founders-4",
            "ot-behaviorism-founders-5"
          ]
        },
        {
          "id": "test-operant-shaping",
          "objectiveId": "obj-operant-shaping",
          "title": "Operant Conditioning & Shaping",
          "mcqIds": [
            "mcq-rw-l2-p1-behaviorism",
            "ot-operant-shaping-1",
            "ot-operant-shaping-2",
            "ot-operant-shaping-3",
            "ot-operant-shaping-4"
          ]
        },
        {
          "id": "test-piaget-processes",
          "objectiveId": "obj-piaget-processes",
          "title": "Piaget's Schema Processes",
          "mcqIds": [
            "mcq-rw-l2-p2-cognitivism",
            "ot-piaget-processes-1",
            "ot-piaget-processes-2",
            "ot-piaget-processes-3",
            "ot-piaget-processes-4"
          ]
        },
        {
          "id": "test-schema-chunking",
          "objectiveId": "obj-schema-chunking",
          "title": "Schemas, Chunking & 7±2",
          "mcqIds": [
            "ot-schema-chunking-1",
            "ot-schema-chunking-2",
            "ot-schema-chunking-3",
            "ot-schema-chunking-4",
            "ot-schema-chunking-5"
          ]
        },
        {
          "id": "test-constructivism",
          "objectiveId": "obj-constructivism",
          "title": "Constructivism, ZPD & Scaffolding",
          "mcqIds": [
            "lt-mcq-mko",
            "ot-constructivism-1",
            "ot-constructivism-2",
            "ot-constructivism-3",
            "ot-constructivism-4"
          ]
        }
      ]
    },
    {
      "id": "l3-bloom-mastery",
      "title": "Bloom's Taxonomy & Mastery Learning",
      "order": 3,
      "studyGuidePath": "/packs/learning-theory/guides/l3-p1-taxonomy.md",
      "sources": [
        {
          "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
        }
      ],
      "parts": [
        {
          "id": "l3-p1-taxonomy",
          "title": "Bloom's taxonomy",
          "order": 1,
          "blurb": "Six cognitive levels, the 1956 original vs 2001 revised names, and the affective domain.",
          "studyGuideAnchor": "bloom-s-taxonomy",
          "itemIds": [
            "lt-fact-blooms-taxonomy",
            "lt-def-blooms-taxonomy",
            "lt-fact-blooms-revision",
            "lt-pair-knowledge-remember",
            "lt-pair-comprehension-understand",
            "lt-pair-synthesis-create",
            "lt-pair-evaluation-evaluate",
            "lt-fact-affective-domain",
            "lt-mcq-affective-levels",
            "czr-learning-theory-lt-def-blooms-taxonomy",
            "cz-learning-theory-lt-fact-affective-domain",
            "tf-d-learning-theory-lt-def-blooms-taxonomy",
            "ot-blooms-structure-1",
            "ot-blooms-structure-2",
            "ot-blooms-structure-3",
            "ot-blooms-structure-4",
            "ot-blooms-structure-5",
            "ot-affective-1",
            "ot-affective-2",
            "ot-affective-3",
            "ot-affective-4",
            "fi-ot-blooms-structure-1",
            "fi-ot-blooms-structure-4"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l3-p1-taxonomy.md"
        },
        {
          "id": "l3-p2-levels-verbs",
          "title": "The verb ladder",
          "order": 2,
          "blurb": "Action verbs per level, climbing Remember to Create, and where Create vs Evaluate sit.",
          "studyGuideAnchor": "the-2001-revision",
          "itemIds": [
            "lt-pair-remember-verbs",
            "lt-pair-apply-verbs",
            "lt-pair-create-verbs",
            "lt-proc-blooms-ladder",
            "lt-mcq-blooms-top",
            "tf-f-learning-theory-lt-pair-remember-verbs",
            "tf-t-learning-theory-lt-pair-apply-verbs",
            "concept-rw-learning-theory-remember",
            "concept-rw-learning-theory-evaluate",
            "concept-rw-learning-theory-create",
            "ot-verb-ladder-1",
            "ot-verb-ladder-2",
            "ot-verb-ladder-3",
            "ot-verb-ladder-4",
            "ot-cov-obj-verb-ladder-1",
            "ot-cov-obj-verb-ladder-2"
          ]
        },
        {
          "id": "l3-p3-two-sigma",
          "title": "The 2 Sigma Problem & mastery learning",
          "order": 3,
          "blurb": "Bloom's 1984 finding, mastery learning, the scalability challenge, and the alterable-variable effect sizes.",
          "studyGuideAnchor": "the-2-sigma-problem-mastery-learning",
          "itemIds": [
            "lt-fact-two-sigma",
            "lt-def-two-sigma-problem",
            "lt-def-mastery-learning",
            "lt-mcq-mastery-threshold",
            "lt-mcq-two-sigma-scalability",
            "lt-num-tutorial-effect",
            "lt-num-reinforcement-effect",
            "lt-num-mastery-effect",
            "lt-num-time-on-task-effect",
            "lt-num-cooperative-effect",
            "lt-num-homework-effect",
            "lt-num-morale-effect",
            "czr-learning-theory-lt-def-two-sigma-problem",
            "czr-learning-theory-lt-def-mastery-learning",
            "cz-learning-theory-lt-fact-two-sigma",
            "tf-d-learning-theory-lt-def-two-sigma-problem",
            "tf-d-learning-theory-lt-def-mastery-learning",
            "ot-two-sigma-1",
            "ot-two-sigma-2",
            "ot-two-sigma-3",
            "ot-alterable-1",
            "ot-alterable-2",
            "ot-alterable-3",
            "ot-alterable-4",
            "ot-alterable-5",
            "fi-lt-mcq-mastery-threshold",
            "fi-ot-two-sigma-3",
            "fi-ot-alterable-2",
            "fi-ot-alterable-3",
            "ot-cov-obj-alterable-variables-1",
            "ot-cov-obj-alterable-variables-2",
            "ot-cov-obj-alterable-variables-3",
            "ot-cov-obj-alterable-variables-4"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l3-p3-two-sigma.md"
        }
      ],
      "objectives": [
        {
          "id": "obj-blooms-structure",
          "statement": "Explain Bloom's Taxonomy and the 2001 revision, including the renaming to verbs and the Synthesis→Create swap at the summit.",
          "demonstrationIds": [
            "d-blooms-revision",
            "d-blooms-def"
          ]
        },
        {
          "id": "obj-affective-domain",
          "statement": "Identify the five levels of Bloom's affective domain (Receiving, Responding, Valuing, Organizing, Characterizing).",
          "demonstrationIds": [
            "d-affective"
          ]
        },
        {
          "id": "obj-verb-ladder",
          "statement": "Match the revised Bloom levels to their action verbs and identify Create as the highest level.",
          "demonstrationIds": [
            "d-verbs",
            "d-level-concepts"
          ]
        },
        {
          "id": "obj-two-sigma-mastery",
          "statement": "Explain the 2 Sigma Problem and mastery learning, including why the result was economically unscalable and how a student's failure is reframed.",
          "demonstrationIds": [
            "d-two-sigma",
            "d-mastery"
          ]
        },
        {
          "id": "obj-alterable-variables",
          "statement": "Rank Bloom's alterable instructional variables by effect size, from one-to-one tutoring down to classroom morale.",
          "demonstrationIds": [
            "d-effect-sizes-1",
            "d-effect-sizes-2"
          ]
        }
      ],
      "demonstrations": [
        {
          "id": "d-blooms-revision",
          "label": "1956→2001 mapping",
          "itemIds": [
            "lt-pair-knowledge-remember",
            "lt-pair-comprehension-understand",
            "lt-pair-synthesis-create",
            "lt-pair-evaluation-evaluate"
          ],
          "requiredCorrect": 4
        },
        {
          "id": "d-blooms-def",
          "label": "Taxonomy definition",
          "itemIds": [
            "lt-def-blooms-taxonomy",
            "czr-learning-theory-lt-def-blooms-taxonomy",
            "tf-d-learning-theory-lt-def-blooms-taxonomy"
          ]
        },
        {
          "id": "d-affective",
          "label": "Affective domain",
          "itemIds": [
            "lt-mcq-affective-levels",
            "cz-learning-theory-lt-fact-affective-domain"
          ]
        },
        {
          "id": "d-verbs",
          "label": "Levels to verbs",
          "itemIds": [
            "lt-pair-remember-verbs",
            "lt-pair-apply-verbs",
            "lt-pair-create-verbs",
            "lt-mcq-blooms-top",
            "ot-cov-obj-verb-ladder-1",
            "ot-cov-obj-verb-ladder-2"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-level-concepts",
          "label": "Level concepts",
          "itemIds": [
            "concept-rw-learning-theory-remember",
            "concept-rw-learning-theory-evaluate",
            "concept-rw-learning-theory-create"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-two-sigma",
          "label": "2 Sigma Problem",
          "itemIds": [
            "lt-def-two-sigma-problem",
            "lt-mcq-two-sigma-scalability",
            "cz-learning-theory-lt-fact-two-sigma",
            "czr-learning-theory-lt-def-two-sigma-problem"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-mastery",
          "label": "Mastery learning",
          "itemIds": [
            "lt-def-mastery-learning",
            "lt-mcq-mastery-threshold",
            "czr-learning-theory-lt-def-mastery-learning"
          ]
        },
        {
          "id": "d-effect-sizes-1",
          "label": "Top effect sizes",
          "itemIds": [
            "lt-num-tutorial-effect",
            "lt-num-reinforcement-effect",
            "lt-num-mastery-effect",
            "lt-num-time-on-task-effect",
            "ot-cov-obj-alterable-variables-1",
            "ot-cov-obj-alterable-variables-2",
            "ot-cov-obj-alterable-variables-3",
            "ot-cov-obj-alterable-variables-4"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-effect-sizes-2",
          "label": "Lower effect sizes",
          "itemIds": [
            "lt-num-cooperative-effect",
            "lt-num-homework-effect",
            "lt-num-morale-effect"
          ],
          "requiredCorrect": 2
        }
      ],
      "objectiveTests": [
        {
          "id": "test-blooms-structure",
          "objectiveId": "obj-blooms-structure",
          "title": "Bloom's Taxonomy & the 2001 Revision",
          "mcqIds": [
            "ot-blooms-structure-1",
            "ot-blooms-structure-2",
            "ot-blooms-structure-3",
            "ot-blooms-structure-4",
            "ot-blooms-structure-5"
          ]
        },
        {
          "id": "test-affective-domain",
          "objectiveId": "obj-affective-domain",
          "title": "The Affective Domain",
          "mcqIds": [
            "lt-mcq-affective-levels",
            "ot-affective-1",
            "ot-affective-2",
            "ot-affective-3",
            "ot-affective-4"
          ]
        },
        {
          "id": "test-verb-ladder",
          "objectiveId": "obj-verb-ladder",
          "title": "The Verb Ladder",
          "mcqIds": [
            "lt-mcq-blooms-top",
            "ot-verb-ladder-1",
            "ot-verb-ladder-2",
            "ot-verb-ladder-3",
            "ot-verb-ladder-4",
            "ot-cov-obj-verb-ladder-1",
            "ot-cov-obj-verb-ladder-2"
          ]
        },
        {
          "id": "test-two-sigma-mastery",
          "objectiveId": "obj-two-sigma-mastery",
          "title": "2 Sigma & Mastery Learning",
          "mcqIds": [
            "lt-mcq-two-sigma-scalability",
            "lt-mcq-mastery-threshold",
            "ot-two-sigma-1",
            "ot-two-sigma-2",
            "ot-two-sigma-3"
          ]
        },
        {
          "id": "test-alterable-variables",
          "objectiveId": "obj-alterable-variables",
          "title": "Alterable Variables by Effect Size",
          "mcqIds": [
            "ot-alterable-1",
            "ot-alterable-2",
            "ot-alterable-3",
            "ot-alterable-4",
            "ot-alterable-5",
            "ot-cov-obj-alterable-variables-1",
            "ot-cov-obj-alterable-variables-2",
            "ot-cov-obj-alterable-variables-3",
            "ot-cov-obj-alterable-variables-4"
          ]
        }
      ]
    },
    {
      "id": "l4-cognitive-science",
      "title": "The Cognitive Science of Learning",
      "order": 4,
      "studyGuidePath": "/packs/learning-theory/guides/l4-p1-flow-dual-coding.md",
      "sources": [
        {
          "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
        }
      ],
      "parts": [
        {
          "id": "l4-p1-flow-dual-coding",
          "title": "Flow & dual coding",
          "order": 1,
          "blurb": "Csikszentmihalyi's flow corridor and Paivio's two memory systems.",
          "studyGuideAnchor": "flow-dual-coding",
          "itemIds": [
            "lt-def-flow",
            "lt-fact-flow-challenge-skill",
            "lt-mcq-flow-too-hard",
            "lt-def-autotelic",
            "lt-num-flow-mastery",
            "lt-num-flow-burnout",
            "lt-def-dual-coding",
            "lt-pair-paivio",
            "czr-learning-theory-lt-def-flow",
            "czr-learning-theory-lt-def-autotelic",
            "czr-learning-theory-lt-def-dual-coding",
            "cz-learning-theory-lt-fact-flow-challenge-skill",
            "mcq-c-learning-theory-lt-fact-flow-challenge-skill",
            "tf-d-learning-theory-lt-def-flow",
            "tf-d-learning-theory-lt-def-autotelic",
            "tf-df-learning-theory-lt-def-dual-coding",
            "concept-rw-learning-theory-allan-paivio",
            "ot-flow-autotelic-1",
            "ot-flow-mastery-2",
            "ot-flow-burnout-3",
            "ot-dual-paivio-1",
            "ot-dual-systems-2",
            "ot-dual-not-3",
            "ot-dual-apply-4",
            "ot-dual-onechannel-5",
            "fi-ot-flow-autotelic-1",
            "fi-ot-flow-mastery-2",
            "fi-ot-dual-paivio-1",
            "fi-ot-dual-systems-2",
            "ot-cov-obj-flow-1",
            "ot-cov-obj-flow-2"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l4-p1-flow-dual-coding.md"
        },
        {
          "id": "l4-p4-cognitive-load",
          "title": "Cognitive load",
          "order": 4,
          "blurb": "Sweller's working-memory limit and the three types of load designers must balance.",
          "studyGuideAnchor": "flow-dual-coding",
          "itemIds": [
            "lt-num-working-memory",
            "lt-def-cognitive-load",
            "lt-def-intrinsic-load",
            "lt-def-extraneous-load",
            "lt-def-germane-load",
            "lt-cmp-intrinsic-extraneous-load",
            "mcq-rw-l4-p4-cognitive-load",
            "czr-learning-theory-lt-def-cognitive-load",
            "czr-learning-theory-lt-def-intrinsic-load",
            "czr-learning-theory-lt-def-extraneous-load",
            "czr-learning-theory-lt-def-germane-load",
            "tf-df-learning-theory-lt-def-cognitive-load",
            "tf-d-learning-theory-lt-def-intrinsic-load",
            "tf-df-learning-theory-lt-def-extraneous-load",
            "tf-d-learning-theory-lt-def-germane-load",
            "ot-load-sweller-1",
            "ot-load-wm-2",
            "ot-load-extraneous-3",
            "ot-load-intrinsic-4"
          ]
        },
        {
          "id": "l4-p2-connectivism-gagne",
          "title": "Connectivism & Gagné's events",
          "order": 2,
          "blurb": "Learning as connecting nodes, and Gagné's nine-step blueprint for designing instruction.",
          "studyGuideAnchor": "connectivism-gagn-s-events",
          "itemIds": [
            "lt-def-connectivism",
            "lt-pair-siemens-downes",
            "lt-fact-know-where",
            "lt-mcq-connectivism-value",
            "lt-mcq-connectivism-gap",
            "lt-pair-gagne",
            "lt-proc-gagne-nine-events",
            "lt-mcq-gagne-outcomes",
            "lt-fact-gagne-five-outcomes",
            "lt-mcq-gagne-first-event",
            "czr-learning-theory-lt-def-connectivism",
            "tf-d-learning-theory-lt-def-connectivism",
            "concept-rw-learning-theory-stephen-downes",
            "concept-rw-learning-theory-robert-gagn",
            "ot-connectivism-authors-1",
            "fi-lt-mcq-connectivism-gap",
            "fi-lt-mcq-gagne-first-event",
            "fi-ot-connectivism-authors-1",
            "ot-cov-obj-connectivism-gagne-1",
            "ot-cov-obj-connectivism-gagne-2",
            "ot-cov-obj-connectivism-gagne-3",
            "ot-cov-obj-connectivism-gagne-4"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l4-p2-connectivism-gagne.md"
        },
        {
          "id": "l4-p3-udl-memory",
          "title": "UDL & memory techniques",
          "order": 3,
          "blurb": "Universal Design for Learning's three principles and the classic mnemonic techniques.",
          "studyGuideAnchor": "udl-memory-techniques",
          "itemIds": [
            "lt-def-udl",
            "lt-pair-udl-representation",
            "lt-pair-udl-action",
            "lt-pair-udl-engagement",
            "lt-mcq-udl-principle",
            "lt-def-method-of-loci",
            "lt-def-keyword-method",
            "lt-fact-mnemonic-images",
            "lt-mcq-loci-leverage",
            "lt-pair-memory-palace-origin",
            "czr-learning-theory-lt-def-udl",
            "czr-learning-theory-lt-def-method-of-loci",
            "czr-learning-theory-lt-def-keyword-method",
            "tf-t-learning-theory-lt-pair-memory-palace-origin",
            "tf-df-learning-theory-lt-def-udl",
            "tf-df-learning-theory-lt-def-method-of-loci",
            "tf-df-learning-theory-lt-def-keyword-method",
            "concept-rw-learning-theory-david-rose",
            "ot-udl-not-1",
            "ot-keyword-method-2",
            "ot-loci-origin-3",
            "fi-lt-mcq-udl-principle",
            "fi-lt-mcq-loci-leverage",
            "fi-ot-keyword-method-2",
            "fi-ot-loci-origin-3",
            "ot-cov-obj-udl-mnemonics-1",
            "ot-cov-obj-udl-mnemonics-2"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l4-p3-udl-memory.md"
        }
      ],
      "objectives": [
        {
          "id": "obj-flow",
          "statement": "Explain flow and the challenge-skill balance — including boredom, anxiety, autotelic engagement, its 1975 origin, and its effects on mastery and burnout.",
          "demonstrationIds": [
            "d-flow-def",
            "d-flow-autotelic"
          ]
        },
        {
          "id": "obj-dual-coding",
          "statement": "Explain Paivio's Dual Coding Theory and its two interconnected verbal and visual memory systems.",
          "demonstrationIds": [
            "d-dual-coding"
          ]
        },
        {
          "id": "obj-cognitive-load",
          "statement": "Distinguish intrinsic, extraneous, and germane cognitive load, and identify which type designers should maximize under Sweller's theory.",
          "demonstrationIds": [
            "d-load-types",
            "d-load-theory"
          ]
        },
        {
          "id": "obj-connectivism-gagne",
          "statement": "Explain connectivism's 'know-where' claim and the gap it named, plus Gagné's five learning outcomes and first event of instruction.",
          "demonstrationIds": [
            "d-connectivism",
            "d-gagne"
          ]
        },
        {
          "id": "obj-udl-mnemonics",
          "statement": "Explain UDL's three principles and the mnemonic techniques (Method of Loci, Keyword Method) that exploit dual coding.",
          "demonstrationIds": [
            "d-udl",
            "d-mnemonics"
          ]
        }
      ],
      "demonstrations": [
        {
          "id": "d-flow-def",
          "label": "Flow & challenge-skill",
          "itemIds": [
            "lt-def-flow",
            "lt-mcq-flow-too-hard",
            "cz-learning-theory-lt-fact-flow-challenge-skill",
            "mcq-c-learning-theory-lt-fact-flow-challenge-skill",
            "ot-cov-obj-flow-1",
            "ot-cov-obj-flow-2"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-flow-autotelic",
          "label": "Autotelic & flow figures",
          "itemIds": [
            "lt-def-autotelic",
            "lt-num-flow-mastery",
            "lt-num-flow-burnout",
            "czr-learning-theory-lt-def-autotelic"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-dual-coding",
          "label": "Dual coding",
          "itemIds": [
            "lt-def-dual-coding",
            "lt-pair-paivio",
            "czr-learning-theory-lt-def-dual-coding",
            "concept-rw-learning-theory-allan-paivio"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-load-types",
          "label": "Load types",
          "itemIds": [
            "lt-def-intrinsic-load",
            "lt-def-extraneous-load",
            "lt-def-germane-load",
            "mcq-rw-l4-p4-cognitive-load"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-load-theory",
          "label": "Cognitive Load Theory",
          "itemIds": [
            "lt-def-cognitive-load",
            "lt-num-working-memory",
            "czr-learning-theory-lt-def-cognitive-load"
          ]
        },
        {
          "id": "d-connectivism",
          "label": "Connectivism",
          "itemIds": [
            "lt-def-connectivism",
            "lt-pair-siemens-downes",
            "lt-mcq-connectivism-value",
            "lt-mcq-connectivism-gap",
            "ot-cov-obj-connectivism-gagne-1",
            "ot-cov-obj-connectivism-gagne-2",
            "ot-cov-obj-connectivism-gagne-3",
            "ot-cov-obj-connectivism-gagne-4"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-gagne",
          "label": "Gagné's model",
          "itemIds": [
            "lt-pair-gagne",
            "lt-mcq-gagne-outcomes",
            "lt-mcq-gagne-first-event"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-udl",
          "label": "UDL principles",
          "itemIds": [
            "lt-def-udl",
            "lt-pair-udl-representation",
            "lt-pair-udl-action",
            "lt-pair-udl-engagement",
            "ot-cov-obj-udl-mnemonics-1",
            "ot-cov-obj-udl-mnemonics-2"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-mnemonics",
          "label": "Loci & keyword",
          "itemIds": [
            "lt-def-method-of-loci",
            "lt-def-keyword-method",
            "lt-mcq-loci-leverage",
            "lt-pair-memory-palace-origin"
          ],
          "requiredCorrect": 3
        }
      ],
      "objectiveTests": [
        {
          "id": "test-flow",
          "objectiveId": "obj-flow",
          "title": "Flow & the Challenge-Skill Balance",
          "mcqIds": [
            "lt-mcq-flow-too-hard",
            "mcq-c-learning-theory-lt-fact-flow-challenge-skill",
            "ot-flow-autotelic-1",
            "ot-flow-mastery-2",
            "ot-flow-burnout-3",
            "ot-cov-obj-flow-1",
            "ot-cov-obj-flow-2"
          ]
        },
        {
          "id": "test-dual-coding",
          "objectiveId": "obj-dual-coding",
          "title": "Dual Coding Theory",
          "mcqIds": [
            "ot-dual-paivio-1",
            "ot-dual-systems-2",
            "ot-dual-not-3",
            "ot-dual-apply-4",
            "ot-dual-onechannel-5"
          ]
        },
        {
          "id": "test-cognitive-load",
          "objectiveId": "obj-cognitive-load",
          "title": "Cognitive Load Theory",
          "mcqIds": [
            "mcq-rw-l4-p4-cognitive-load",
            "ot-load-sweller-1",
            "ot-load-wm-2",
            "ot-load-extraneous-3",
            "ot-load-intrinsic-4"
          ]
        },
        {
          "id": "test-connectivism-gagne",
          "objectiveId": "obj-connectivism-gagne",
          "title": "Connectivism & Gagné",
          "mcqIds": [
            "lt-mcq-connectivism-value",
            "lt-mcq-connectivism-gap",
            "lt-mcq-gagne-outcomes",
            "lt-mcq-gagne-first-event",
            "ot-connectivism-authors-1",
            "ot-cov-obj-connectivism-gagne-1",
            "ot-cov-obj-connectivism-gagne-2",
            "ot-cov-obj-connectivism-gagne-3",
            "ot-cov-obj-connectivism-gagne-4"
          ]
        },
        {
          "id": "test-udl-mnemonics",
          "objectiveId": "obj-udl-mnemonics",
          "title": "UDL & Memory Techniques",
          "mcqIds": [
            "lt-mcq-udl-principle",
            "lt-mcq-loci-leverage",
            "ot-udl-not-1",
            "ot-keyword-method-2",
            "ot-loci-origin-3",
            "ot-cov-obj-udl-mnemonics-1",
            "ot-cov-obj-udl-mnemonics-2"
          ]
        }
      ]
    },
    {
      "id": "l5-instructional-design",
      "title": "Instructional Design Frameworks",
      "order": 5,
      "studyGuidePath": "/packs/learning-theory/guides/l5-p1-addie.md",
      "sources": [
        {
          "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
        }
      ],
      "parts": [
        {
          "id": "l5-p1-addie",
          "title": "The ADDIE model",
          "order": 1,
          "blurb": "The five phases, waterfall versus iterative, and what 'evaluate' really means.",
          "studyGuideAnchor": "the-addie-model",
          "itemIds": [
            "lt-fact-addie-origin",
            "lt-def-addie",
            "lt-proc-addie",
            "lt-pair-addie-analyze",
            "lt-pair-addie-design",
            "lt-pair-addie-develop",
            "lt-cmp-addie-waterfall-iterative",
            "lt-cmp-formative-summative",
            "lt-fact-addie-rigidity",
            "mcq-rw-l5-p1-addie",
            "czr-learning-theory-lt-def-addie",
            "cz-learning-theory-lt-fact-addie-origin",
            "tf-f-learning-theory-lt-pair-addie-analyze",
            "tf-f-learning-theory-lt-pair-addie-design",
            "tf-t-learning-theory-lt-pair-addie-develop",
            "tf-df-learning-theory-lt-def-addie",
            "ot-addie-phases-1",
            "ot-addie-phases-2",
            "ot-addie-phases-3",
            "ot-addie-phases-4",
            "ot-addie-phases-5",
            "ot-addie-eval-1",
            "ot-addie-eval-2",
            "ot-addie-eval-3",
            "ot-addie-eval-4",
            "fi-mcq-rw-l5-p1-addie",
            "fi-ot-addie-phases-3",
            "fi-ot-addie-phases-5"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l5-p1-addie.md"
        },
        {
          "id": "l5-p2-frameworks-socratic",
          "title": "ID frameworks & the Socratic method",
          "order": 2,
          "blurb": "Five rival design frameworks, then the oldest trick in teaching: questions over answers.",
          "studyGuideAnchor": "id-frameworks-the-socratic-method",
          "itemIds": [
            "lt-pair-dick-carey",
            "lt-pair-sam",
            "lt-pair-merrill",
            "lt-pair-ubd",
            "lt-def-backward-design",
            "lt-def-action-mapping",
            "lt-mcq-backward-design",
            "lt-def-socratic-method",
            "lt-cmp-direct-socratic",
            "lt-fact-khanmigo-socratic",
            "czr-learning-theory-lt-def-backward-design",
            "czr-learning-theory-lt-def-action-mapping",
            "czr-learning-theory-lt-def-socratic-method",
            "cz-learning-theory-lt-fact-khanmigo-socratic",
            "tf-t-learning-theory-lt-pair-merrill",
            "tf-d-learning-theory-lt-def-backward-design",
            "tf-df-learning-theory-lt-def-action-mapping",
            "tf-d-learning-theory-lt-def-socratic-method",
            "concept-rw-learning-theory-sam-successive-approximation-model",
            "concept-rw-learning-theory-dick-carey-model",
            "concept-rw-learning-theory-merrill-s-principles-of-instruction",
            "concept-rw-learning-theory-understanding-by-design-ubd",
            "concept-rw-learning-theory-action-mapping",
            "ot-frameworks-1",
            "ot-frameworks-2",
            "ot-frameworks-3",
            "ot-frameworks-4",
            "ot-frameworks-5",
            "ot-backward-action-1",
            "ot-backward-action-2",
            "ot-backward-action-3",
            "ot-backward-action-4",
            "ot-socratic-1",
            "ot-socratic-2",
            "ot-socratic-3",
            "ot-socratic-4",
            "ot-socratic-5",
            "fi-lt-mcq-backward-design",
            "fi-ot-frameworks-1",
            "fi-ot-frameworks-2",
            "fi-ot-frameworks-3"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l5-p2-frameworks-socratic.md"
        }
      ],
      "objectives": [
        {
          "id": "obj-addie-phases",
          "statement": "Identify ADDIE's origin and sequence its five phases, matching Analyze, Design, and Develop to their functions.",
          "demonstrationIds": [
            "d-addie-phases",
            "d-addie-origin"
          ]
        },
        {
          "id": "obj-addie-evaluate",
          "statement": "Explain how the Evaluate phase threads through all of ADDIE rather than acting as a final gate.",
          "demonstrationIds": [
            "d-addie-evaluate"
          ]
        },
        {
          "id": "obj-id-frameworks",
          "statement": "Match the major instructional-design frameworks (Dick & Carey, SAM, Merrill, UbD) to their defining approach.",
          "demonstrationIds": [
            "d-frameworks",
            "d-framework-concepts"
          ]
        },
        {
          "id": "obj-backward-vs-action",
          "statement": "Distinguish backward design (Wiggins & McTighe's UbD) from Cathy Moore's Action Mapping.",
          "demonstrationIds": [
            "d-backward-vs-action",
            "d-backward-detail"
          ]
        },
        {
          "id": "obj-socratic",
          "statement": "Explain the Socratic method and how Khanmigo embodies it through guided questioning rather than direct answers.",
          "demonstrationIds": [
            "d-socratic"
          ]
        }
      ],
      "demonstrations": [
        {
          "id": "d-addie-phases",
          "label": "ADDIE phases",
          "itemIds": [
            "lt-pair-addie-analyze",
            "lt-pair-addie-design",
            "lt-pair-addie-develop"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-addie-origin",
          "label": "ADDIE origin",
          "itemIds": [
            "lt-def-addie",
            "cz-learning-theory-lt-fact-addie-origin"
          ]
        },
        {
          "id": "d-addie-evaluate",
          "label": "Evaluate phase",
          "itemIds": [
            "mcq-rw-l5-p1-addie",
            "czr-learning-theory-lt-def-addie",
            "tf-df-learning-theory-lt-def-addie"
          ]
        },
        {
          "id": "d-frameworks",
          "label": "Frameworks matched",
          "itemIds": [
            "lt-pair-dick-carey",
            "lt-pair-sam",
            "lt-pair-merrill",
            "lt-pair-ubd"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-framework-concepts",
          "label": "Framework recognition",
          "itemIds": [
            "concept-rw-learning-theory-sam-successive-approximation-model",
            "concept-rw-learning-theory-dick-carey-model",
            "concept-rw-learning-theory-merrill-s-principles-of-instruction",
            "concept-rw-learning-theory-understanding-by-design-ubd"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-backward-vs-action",
          "label": "Backward vs Action",
          "itemIds": [
            "lt-def-backward-design",
            "lt-def-action-mapping",
            "lt-mcq-backward-design"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-backward-detail",
          "label": "Attribution detail",
          "itemIds": [
            "czr-learning-theory-lt-def-backward-design",
            "czr-learning-theory-lt-def-action-mapping",
            "concept-rw-learning-theory-action-mapping"
          ]
        },
        {
          "id": "d-socratic",
          "label": "Socratic method & Khanmigo",
          "itemIds": [
            "lt-def-socratic-method",
            "czr-learning-theory-lt-def-socratic-method",
            "cz-learning-theory-lt-fact-khanmigo-socratic"
          ]
        }
      ],
      "objectiveTests": [
        {
          "id": "test-addie-phases",
          "objectiveId": "obj-addie-phases",
          "title": "ADDIE: Origin & Phases",
          "mcqIds": [
            "ot-addie-phases-1",
            "ot-addie-phases-2",
            "ot-addie-phases-3",
            "ot-addie-phases-4",
            "ot-addie-phases-5"
          ]
        },
        {
          "id": "test-addie-evaluate",
          "objectiveId": "obj-addie-evaluate",
          "title": "ADDIE: The Evaluate Phase",
          "mcqIds": [
            "mcq-rw-l5-p1-addie",
            "ot-addie-eval-1",
            "ot-addie-eval-2",
            "ot-addie-eval-3",
            "ot-addie-eval-4"
          ]
        },
        {
          "id": "test-id-frameworks",
          "objectiveId": "obj-id-frameworks",
          "title": "ID Frameworks Matching",
          "mcqIds": [
            "ot-frameworks-1",
            "ot-frameworks-2",
            "ot-frameworks-3",
            "ot-frameworks-4",
            "ot-frameworks-5"
          ]
        },
        {
          "id": "test-backward-vs-action",
          "objectiveId": "obj-backward-vs-action",
          "title": "Backward Design vs Action Mapping",
          "mcqIds": [
            "lt-mcq-backward-design",
            "ot-backward-action-1",
            "ot-backward-action-2",
            "ot-backward-action-3",
            "ot-backward-action-4"
          ]
        },
        {
          "id": "test-socratic",
          "objectiveId": "obj-socratic",
          "title": "Socratic Method & Khanmigo",
          "mcqIds": [
            "ot-socratic-1",
            "ot-socratic-2",
            "ot-socratic-3",
            "ot-socratic-4",
            "ot-socratic-5"
          ]
        }
      ]
    },
    {
      "id": "l6-brave-new-words",
      "title": "Brave New Words: AI & Education",
      "order": 6,
      "studyGuidePath": "/packs/learning-theory/guides/l6-p1-khan-vision.md",
      "sources": [
        {
          "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
        }
      ],
      "parts": [
        {
          "id": "l6-p1-khan-vision",
          "title": "Khan's vision",
          "order": 1,
          "blurb": "The 2024 book, the sci-fi that inspired it, and AI reframed as an equalizer.",
          "studyGuideAnchor": "khan-s-vision",
          "itemIds": [
            "lt-fact-brave-new-words",
            "lt-def-personalization-problem",
            "lt-fact-chatgpt-panic",
            "lt-pair-diamond-age",
            "lt-pair-enders-game",
            "lt-pair-fun-they-had",
            "lt-mcq-three-inspirations",
            "lt-fact-equity-engine",
            "czr-learning-theory-lt-def-personalization-problem",
            "tf-f-learning-theory-lt-pair-diamond-age",
            "tf-f-learning-theory-lt-pair-enders-game",
            "tf-f-learning-theory-lt-pair-fun-they-had",
            "tf-d-learning-theory-lt-def-personalization-problem",
            "concept-rw-learning-theory-the-diamond-age",
            "concept-rw-learning-theory-ender-s-game",
            "concept-rw-learning-theory-the-fun-they-had",
            "ot-personalization-1",
            "ot-personalization-2",
            "ot-personalization-3",
            "ot-personalization-4",
            "ot-personalization-5",
            "ot-scifi-1",
            "ot-scifi-2",
            "ot-scifi-3",
            "ot-scifi-4",
            "fi-ot-personalization-1",
            "fi-ot-personalization-2",
            "ot-cov-obj-scifi-inspirations-1"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l6-p1-khan-vision.md"
        },
        {
          "id": "l6-p2-khanmigo-debate",
          "title": "Khanmigo & the debate",
          "order": 2,
          "blurb": "The Socratic tutor built on GPT-4, the ethical caveats, and the contrarian critique.",
          "studyGuideAnchor": "khanmigo-the-debate",
          "itemIds": [
            "lt-def-khanmigo",
            "lt-fact-khanmigo-name",
            "lt-pair-conmigo",
            "lt-cmp-cheating-vs-equalizer",
            "lt-fact-beyond-classroom",
            "lt-fact-ethical-framework",
            "lt-fact-warner-critique",
            "mcq-rw-l6-p2-khanmigo-debate",
            "czr-learning-theory-lt-def-khanmigo",
            "cz-learning-theory-lt-fact-khanmigo-name",
            "cz-learning-theory-lt-fact-beyond-classroom",
            "tf-d-learning-theory-lt-def-khanmigo",
            "ot-khanmigo-1",
            "ot-khanmigo-2",
            "ot-khanmigo-3",
            "ot-khanmigo-4",
            "ot-khanmigo-5",
            "ot-stakes-1",
            "ot-stakes-2",
            "ot-stakes-4",
            "ot-stakes-5",
            "fi-ot-khanmigo-2"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l6-p2-khanmigo-debate.md"
        }
      ],
      "objectives": [
        {
          "id": "obj-personalization",
          "statement": "Explain the personalization problem that Khan argues AI tutoring can finally solve.",
          "demonstrationIds": [
            "d-personalization"
          ]
        },
        {
          "id": "obj-scifi-inspirations",
          "statement": "Match Khan's three sci-fi inspirations to their educational vision and identify the work that is NOT an inspiration.",
          "demonstrationIds": [
            "d-scifi",
            "d-scifi-concepts"
          ]
        },
        {
          "id": "obj-khanmigo",
          "statement": "Explain Khanmigo — its GPT-4/OpenAI basis, Socratic design, and the 'conmigo' pun behind its name.",
          "demonstrationIds": [
            "d-khanmigo"
          ]
        },
        {
          "id": "obj-stakes-critique",
          "statement": "Recognize the book's stakes beyond K-12 and John Warner's contrarian critique of technology optimism.",
          "demonstrationIds": [
            "d-stakes-critique"
          ]
        }
      ],
      "demonstrations": [
        {
          "id": "d-personalization",
          "label": "Personalization problem",
          "itemIds": [
            "lt-def-personalization-problem",
            "czr-learning-theory-lt-def-personalization-problem",
            "tf-d-learning-theory-lt-def-personalization-problem"
          ]
        },
        {
          "id": "d-scifi",
          "label": "Sci-fi inspirations",
          "itemIds": [
            "lt-pair-diamond-age",
            "lt-pair-enders-game",
            "lt-pair-fun-they-had",
            "lt-mcq-three-inspirations",
            "ot-cov-obj-scifi-inspirations-1"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-scifi-concepts",
          "label": "Fiction recognition",
          "itemIds": [
            "concept-rw-learning-theory-the-diamond-age",
            "concept-rw-learning-theory-ender-s-game",
            "concept-rw-learning-theory-the-fun-they-had"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-khanmigo",
          "label": "Khanmigo",
          "itemIds": [
            "lt-def-khanmigo",
            "lt-pair-conmigo",
            "czr-learning-theory-lt-def-khanmigo",
            "cz-learning-theory-lt-fact-khanmigo-name"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-stakes-critique",
          "label": "Stakes & critique",
          "itemIds": [
            "cz-learning-theory-lt-fact-beyond-classroom",
            "mcq-rw-l6-p2-khanmigo-debate"
          ]
        }
      ],
      "objectiveTests": [
        {
          "id": "test-personalization",
          "objectiveId": "obj-personalization",
          "title": "The Personalization Problem",
          "mcqIds": [
            "ot-personalization-1",
            "ot-personalization-2",
            "ot-personalization-3",
            "ot-personalization-4",
            "ot-personalization-5"
          ]
        },
        {
          "id": "test-scifi-inspirations",
          "objectiveId": "obj-scifi-inspirations",
          "title": "Khan's Sci-Fi Touchstones",
          "mcqIds": [
            "lt-mcq-three-inspirations",
            "ot-scifi-1",
            "ot-scifi-2",
            "ot-scifi-3",
            "ot-scifi-4",
            "ot-cov-obj-scifi-inspirations-1"
          ]
        },
        {
          "id": "test-khanmigo",
          "objectiveId": "obj-khanmigo",
          "title": "Khanmigo: Build & Design",
          "mcqIds": [
            "ot-khanmigo-1",
            "ot-khanmigo-2",
            "ot-khanmigo-3",
            "ot-khanmigo-4",
            "ot-khanmigo-5"
          ]
        },
        {
          "id": "test-stakes-critique",
          "objectiveId": "obj-stakes-critique",
          "title": "Beyond K-12 & the Critique",
          "mcqIds": [
            "mcq-rw-l6-p2-khanmigo-debate",
            "ot-stakes-1",
            "ot-stakes-2",
            "ot-stakes-4",
            "ot-stakes-5"
          ]
        }
      ]
    },
    {
      "id": "l7-edtech-landscape",
      "title": "The Modern EdTech Landscape",
      "order": 7,
      "studyGuidePath": "/packs/learning-theory/guides/l7-p1-taxonomy.md",
      "sources": [
        {
          "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
        }
      ],
      "parts": [
        {
          "id": "l7-p1-taxonomy",
          "title": "The AI platform taxonomy",
          "order": 1,
          "blurb": "Eight categories of AI-in-education and the players who lead each.",
          "studyGuideAnchor": "the-ai-platform-taxonomy",
          "itemIds": [
            "lt-fact-ai-taxonomy",
            "lt-pair-tutors-khanmigo",
            "lt-pair-teachertools-magicschool",
            "lt-pair-language-duolingo",
            "lt-pair-research-notebooklm",
            "lt-pair-enterprise-sana",
            "lt-pair-assessment-gradescope",
            "lt-pair-gamelearning-kahoot",
            "lt-mcq-taxonomy-notebooklm",
            "tf-f-learning-theory-lt-pair-tutors-khanmigo",
            "tf-t-learning-theory-lt-pair-teachertools-magicschool",
            "tf-f-learning-theory-lt-pair-language-duolingo",
            "tf-f-learning-theory-lt-pair-research-notebooklm",
            "ot-taxonomy-1",
            "ot-taxonomy-2",
            "ot-taxonomy-5",
            "ot-taxonomy-3",
            "ot-taxonomy-4",
            "fi-lt-mcq-taxonomy-notebooklm",
            "fi-ot-taxonomy-1",
            "fi-ot-taxonomy-2",
            "fi-ot-taxonomy-5"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l7-p1-taxonomy.md"
        },
        {
          "id": "l7-p2-platforms",
          "title": "Platform deep-dives",
          "order": 2,
          "blurb": "Khanmigo, Duolingo, MagicSchool, Synthesis, and NotebookLM up close.",
          "studyGuideAnchor": "platform-deep-dives",
          "itemIds": [
            "lt-fact-khanmigo",
            "lt-num-khanmigo-students",
            "lt-mcq-khanmigo-method",
            "lt-fact-duolingo-birdbrain",
            "lt-pair-duolingo-birdbrain",
            "lt-fact-magicschool",
            "lt-fact-synthesis",
            "lt-def-adaptive-learning",
            "lt-mcq-synthesis-origin",
            "lt-fact-notebooklm",
            "czr-learning-theory-lt-def-adaptive-learning",
            "tf-t-learning-theory-lt-pair-duolingo-birdbrain",
            "tf-df-learning-theory-lt-def-adaptive-learning",
            "concept-rw-learning-theory-khanmigo",
            "concept-rw-learning-theory-duolingo",
            "concept-rw-learning-theory-magicschool-ai",
            "concept-rw-learning-theory-synthesis",
            "concept-rw-learning-theory-google-notebooklm",
            "ot-platforms-1",
            "ot-platforms-2",
            "ot-platforms-3",
            "ot-platcat-1",
            "ot-platcat-2",
            "ot-platcat-4",
            "ot-platcat-3",
            "ot-cov-obj-platforms-1",
            "ot-cov-obj-platforms-2",
            "ot-cov-obj-platforms-3",
            "ot-cov-obj-platforms-4"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l7-p2-platforms.md"
        },
        {
          "id": "l7-p3-evidence",
          "title": "Does AI tutoring work?",
          "order": 3,
          "blurb": "The randomized trials and meta-analyses behind the AI-tutoring claims.",
          "studyGuideAnchor": "does-ai-tutoring-work",
          "itemIds": [
            "lt-def-intelligent-tutoring",
            "lt-fact-meta-analysis",
            "lt-fact-learnlm-rct",
            "lt-num-learnlm-success",
            "lt-num-humantutor-success",
            "lt-num-statichints-success",
            "lt-fact-tutor-copilot",
            "lt-mcq-tutor-copilot-floor",
            "lt-fact-brookings",
            "czr-learning-theory-lt-def-intelligent-tutoring",
            "tf-d-learning-theory-lt-def-intelligent-tutoring",
            "ot-evidence-1",
            "ot-evidence-3",
            "ot-evidence-4",
            "ot-evidence-2",
            "fi-ot-evidence-4"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l7-p3-evidence.md"
        },
        {
          "id": "l7-p4-market",
          "title": "The adaptive-learning market",
          "order": 4,
          "blurb": "The dollars, the deals, and what 2026 investors now demand.",
          "studyGuideAnchor": "the-adaptive-learning-market",
          "itemIds": [
            "lt-fact-market-size",
            "lt-num-market-2025",
            "lt-num-market-2032",
            "lt-num-edtech-investment-2025",
            "lt-num-workday-sana",
            "lt-num-coursera-udemy",
            "lt-fact-sector-split",
            "lt-cmp-engagement-vs-outcomes",
            "lt-fact-2026-projections",
            "mcq-rw-l7-p4-market",
            "ot-market-1",
            "ot-market-2",
            "ot-market-3",
            "ot-market-4",
            "fi-ot-market-2",
            "fi-ot-market-3",
            "ot-cov-obj-market-1",
            "ot-cov-obj-market-2"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l7-p4-market.md"
        }
      ],
      "objectives": [
        {
          "id": "obj-taxonomy",
          "statement": "Classify AI-in-education products into the seven functional categories by what each actually does.",
          "demonstrationIds": [
            "d-taxonomy-a",
            "d-taxonomy-b"
          ]
        },
        {
          "id": "obj-platforms",
          "statement": "Describe how the flagship platforms work — Khanmigo's Socratic method and scale, Duolingo BirdBrain, Synthesis's origin — and define adaptive learning.",
          "demonstrationIds": [
            "d-khanmigo-platform",
            "d-adaptive-platforms"
          ]
        },
        {
          "id": "obj-evidence",
          "statement": "Evaluate the RCT evidence for AI tutoring, comparing LearnLM, human-tutor, and static-hint success rates and who benefits most.",
          "demonstrationIds": [
            "d-rct",
            "d-its"
          ]
        },
        {
          "id": "obj-market",
          "statement": "Quantify the adaptive-learning market and the major 2025 EdTech deals and investment.",
          "demonstrationIds": [
            "d-market",
            "d-deals"
          ]
        },
        {
          "id": "obj-platform-categories",
          "statement": "Match each named platform (Khanmigo, Duolingo, MagicSchool, Synthesis, NotebookLM) to its edtech category.",
          "demonstrationIds": [
            "d-platform-categories",
            "d-notebooklm-category"
          ]
        }
      ],
      "demonstrations": [
        {
          "id": "d-taxonomy-a",
          "label": "Categories 1-4",
          "itemIds": [
            "lt-pair-tutors-khanmigo",
            "lt-pair-teachertools-magicschool",
            "lt-pair-language-duolingo",
            "lt-pair-research-notebooklm"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-taxonomy-b",
          "label": "Categories 5-7",
          "itemIds": [
            "lt-pair-enterprise-sana",
            "lt-pair-assessment-gradescope",
            "lt-pair-gamelearning-kahoot",
            "lt-mcq-taxonomy-notebooklm"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-khanmigo-platform",
          "label": "Khanmigo platform",
          "itemIds": [
            "lt-num-khanmigo-students",
            "lt-mcq-khanmigo-method",
            "ot-cov-obj-platforms-1",
            "ot-cov-obj-platforms-2",
            "ot-cov-obj-platforms-3",
            "ot-cov-obj-platforms-4"
          ]
        },
        {
          "id": "d-adaptive-platforms",
          "label": "Adaptive platforms",
          "itemIds": [
            "lt-def-adaptive-learning",
            "lt-pair-duolingo-birdbrain",
            "lt-mcq-synthesis-origin",
            "czr-learning-theory-lt-def-adaptive-learning"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-rct",
          "label": "LearnLM RCT rates",
          "itemIds": [
            "lt-num-learnlm-success",
            "lt-num-humantutor-success",
            "lt-num-statichints-success"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-its",
          "label": "ITS & Tutor CoPilot",
          "itemIds": [
            "lt-def-intelligent-tutoring",
            "lt-mcq-tutor-copilot-floor",
            "czr-learning-theory-lt-def-intelligent-tutoring"
          ]
        },
        {
          "id": "d-market",
          "label": "Market size",
          "itemIds": [
            "lt-num-market-2025",
            "lt-num-market-2032",
            "lt-num-edtech-investment-2025",
            "ot-cov-obj-market-1",
            "ot-cov-obj-market-2"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-deals",
          "label": "2025 deals",
          "itemIds": [
            "lt-num-workday-sana",
            "lt-num-coursera-udemy",
            "mcq-rw-l7-p4-market"
          ]
        },
        {
          "id": "d-platform-categories",
          "label": "Platform categories",
          "itemIds": [
            "concept-rw-learning-theory-khanmigo",
            "concept-rw-learning-theory-duolingo",
            "concept-rw-learning-theory-magicschool-ai",
            "concept-rw-learning-theory-synthesis"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-notebooklm-category",
          "label": "NotebookLM category",
          "itemIds": [
            "concept-rw-learning-theory-google-notebooklm",
            "lt-mcq-taxonomy-notebooklm"
          ]
        }
      ],
      "objectiveTests": [
        {
          "id": "test-taxonomy",
          "objectiveId": "obj-taxonomy",
          "title": "The Seven EdTech Categories",
          "mcqIds": [
            "ot-taxonomy-1",
            "ot-taxonomy-2",
            "ot-taxonomy-5",
            "ot-taxonomy-3",
            "ot-taxonomy-4"
          ]
        },
        {
          "id": "test-platforms",
          "objectiveId": "obj-platforms",
          "title": "Flagship Platforms & Adaptive Learning",
          "mcqIds": [
            "lt-mcq-khanmigo-method",
            "lt-mcq-synthesis-origin",
            "ot-platforms-1",
            "ot-platforms-2",
            "ot-platforms-3",
            "ot-cov-obj-platforms-1",
            "ot-cov-obj-platforms-2",
            "ot-cov-obj-platforms-3",
            "ot-cov-obj-platforms-4"
          ]
        },
        {
          "id": "test-evidence",
          "objectiveId": "obj-evidence",
          "title": "The RCT Evidence for AI Tutoring",
          "mcqIds": [
            "lt-mcq-tutor-copilot-floor",
            "ot-evidence-1",
            "ot-evidence-3",
            "ot-evidence-4",
            "ot-evidence-2"
          ]
        },
        {
          "id": "test-market",
          "objectiveId": "obj-market",
          "title": "Market Size & 2025 Deals",
          "mcqIds": [
            "mcq-rw-l7-p4-market",
            "ot-market-1",
            "ot-market-2",
            "ot-market-3",
            "ot-market-4",
            "ot-cov-obj-market-1",
            "ot-cov-obj-market-2"
          ]
        },
        {
          "id": "test-platform-categories",
          "objectiveId": "obj-platform-categories",
          "title": "Match Platform to Category",
          "mcqIds": [
            "lt-mcq-taxonomy-notebooklm",
            "ot-platcat-1",
            "ot-platcat-2",
            "ot-platcat-4",
            "ot-platcat-3"
          ]
        }
      ]
    },
    {
      "id": "l8-lms-gamification",
      "title": "LMS, Standards & Gamification",
      "order": 8,
      "studyGuidePath": "/packs/learning-theory/guides/l8-p1-lms-history.md",
      "sources": [
        {
          "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
        }
      ],
      "parts": [
        {
          "id": "l8-p1-lms-history",
          "title": "LMS history & leaders",
          "order": 1,
          "blurb": "From Pressey's 1924 teaching machine through Moodle to today's AI-integrated platforms.",
          "studyGuideAnchor": "lms-history-leaders",
          "itemIds": [
            "lt-fact-lms-lineage",
            "lt-proc-lms-evolution",
            "lt-num-lms-years",
            "lt-num-plato",
            "lt-num-scorm",
            "lt-num-moodle",
            "lt-mcq-canvas",
            "concept-rw-learning-theory-plato",
            "concept-rw-learning-theory-moodle",
            "concept-rw-learning-theory-canvas",
            "concept-rw-learning-theory-blackboard",
            "ot-lms-history-1",
            "ot-lms-history-2",
            "ot-lms-history-3",
            "ot-lms-history-4",
            "ot-lms-history-5",
            "ot-lms-platforms-1",
            "ot-lms-platforms-2",
            "ot-lms-platforms-3",
            "ot-lms-platforms-4",
            "fi-lt-mcq-canvas",
            "fi-ot-lms-history-2",
            "fi-ot-lms-history-4",
            "fi-ot-lms-platforms-3"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l8-p1-lms-history.md"
        },
        {
          "id": "l8-p2-standards",
          "title": "Interoperability standards",
          "order": 2,
          "blurb": "SCORM, xAPI and the Learning Record Store — what each one actually tracks.",
          "studyGuideAnchor": "lms-history-leaders",
          "itemIds": [
            "lt-def-scorm",
            "lt-def-xapi",
            "lt-def-lrs",
            "lt-pair-scorm-tracks",
            "lt-pair-xapi-tracks",
            "lt-pair-lrs-role",
            "lt-mcq-xapi-statement",
            "lt-cmp-scorm-xapi",
            "czr-learning-theory-lt-def-xapi",
            "czr-learning-theory-lt-def-scorm",
            "czr-learning-theory-lt-def-lrs",
            "tf-t-learning-theory-lt-pair-scorm-tracks",
            "tf-f-learning-theory-lt-pair-lrs-role",
            "tf-d-learning-theory-lt-def-xapi",
            "tf-d-learning-theory-lt-def-scorm",
            "tf-df-learning-theory-lt-def-lrs",
            "ot-interop-1",
            "ot-interop-2",
            "ot-interop-3",
            "ot-interop-4",
            "ot-cov-obj-interop-standards-1",
            "ot-cov-obj-interop-standards-2"
          ]
        },
        {
          "id": "l8-p3-gamification",
          "title": "Gamification & motivation",
          "order": 3,
          "blurb": "Game elements in learning, the thinkers behind them, and the intrinsic-vs-extrinsic trap.",
          "studyGuideAnchor": "gamification-motivation",
          "itemIds": [
            "lt-def-gamification",
            "lt-fact-gamification-origins",
            "lt-pair-schell",
            "lt-pair-mcgonigal",
            "lt-pair-kapp",
            "lt-pair-salen-zimmerman",
            "lt-mcq-mechanics",
            "lt-def-sdt",
            "lt-def-autotelic",
            "lt-cmp-intrinsic-extrinsic",
            "czr-learning-theory-lt-def-sdt",
            "czr-learning-theory-lt-def-gamification",
            "tf-df-learning-theory-lt-def-sdt",
            "tf-df-learning-theory-lt-def-gamification",
            "ot-gamification-1",
            "ot-gamification-2",
            "ot-gamification-3",
            "ot-gamification-4",
            "ot-sdt-1",
            "ot-sdt-2",
            "ot-sdt-3",
            "ot-sdt-4",
            "ot-sdt-5",
            "fi-lt-mcq-mechanics",
            "fi-ot-gamification-2",
            "fi-ot-sdt-2",
            "fi-ot-sdt-5"
          ],
          "studyGuidePath": "/packs/learning-theory/guides/l8-p3-gamification.md"
        }
      ],
      "objectives": [
        {
          "id": "obj-lms-history",
          "statement": "Sequence the milestone years of LMS evolution — Pressey's machine, PLATO, SCORM, and Moodle.",
          "demonstrationIds": [
            "d-lms-dates"
          ]
        },
        {
          "id": "obj-lms-platforms",
          "statement": "Recognize the major LMS platforms (PLATO, Moodle, Canvas, Blackboard) and Canvas's rise over Blackboard.",
          "demonstrationIds": [
            "d-lms-platforms",
            "d-canvas"
          ]
        },
        {
          "id": "obj-interop-standards",
          "statement": "Distinguish SCORM from xAPI and explain the role of the Learning Record Store, including xAPI's Actor-Verb-Object statements.",
          "demonstrationIds": [
            "d-scorm-xapi",
            "d-lrs"
          ]
        },
        {
          "id": "obj-gamification",
          "statement": "Define gamification and match its key thinkers to their works, including the mechanic that reframes failure as information.",
          "demonstrationIds": [
            "d-gamification-def",
            "d-gamification-thinkers"
          ]
        },
        {
          "id": "obj-sdt",
          "statement": "Explain Self-Determination Theory's three needs and autotelic, intrinsic motivation.",
          "demonstrationIds": [
            "d-sdt"
          ]
        }
      ],
      "demonstrations": [
        {
          "id": "d-lms-dates",
          "label": "LMS milestone years",
          "itemIds": [
            "lt-num-lms-years",
            "lt-num-plato",
            "lt-num-scorm",
            "lt-num-moodle"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-lms-platforms",
          "label": "LMS platforms",
          "itemIds": [
            "concept-rw-learning-theory-plato",
            "concept-rw-learning-theory-moodle",
            "concept-rw-learning-theory-canvas",
            "concept-rw-learning-theory-blackboard"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-canvas",
          "label": "Canvas vs Blackboard",
          "itemIds": [
            "lt-mcq-canvas",
            "concept-rw-learning-theory-canvas"
          ]
        },
        {
          "id": "d-scorm-xapi",
          "label": "SCORM vs xAPI",
          "itemIds": [
            "lt-def-scorm",
            "lt-def-xapi",
            "lt-pair-scorm-tracks",
            "lt-pair-xapi-tracks",
            "ot-cov-obj-interop-standards-1",
            "ot-cov-obj-interop-standards-2"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-lrs",
          "label": "LRS & statements",
          "itemIds": [
            "lt-def-lrs",
            "lt-pair-lrs-role",
            "lt-mcq-xapi-statement",
            "czr-learning-theory-lt-def-lrs"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-gamification-def",
          "label": "Gamification defined",
          "itemIds": [
            "lt-def-gamification",
            "czr-learning-theory-lt-def-gamification",
            "lt-mcq-mechanics"
          ]
        },
        {
          "id": "d-gamification-thinkers",
          "label": "Gamification thinkers",
          "itemIds": [
            "lt-pair-schell",
            "lt-pair-mcgonigal",
            "lt-pair-kapp",
            "lt-pair-salen-zimmerman"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-sdt",
          "label": "SDT & autotelic",
          "itemIds": [
            "lt-def-sdt",
            "lt-def-autotelic",
            "czr-learning-theory-lt-def-sdt",
            "tf-df-learning-theory-lt-def-sdt"
          ],
          "requiredCorrect": 3
        }
      ],
      "objectiveTests": [
        {
          "id": "test-lms-history",
          "objectiveId": "obj-lms-history",
          "title": "LMS Milestone Years",
          "mcqIds": [
            "ot-lms-history-1",
            "ot-lms-history-2",
            "ot-lms-history-3",
            "ot-lms-history-4",
            "ot-lms-history-5"
          ]
        },
        {
          "id": "test-lms-platforms",
          "objectiveId": "obj-lms-platforms",
          "title": "Major LMS Platforms",
          "mcqIds": [
            "lt-mcq-canvas",
            "ot-lms-platforms-1",
            "ot-lms-platforms-2",
            "ot-lms-platforms-3",
            "ot-lms-platforms-4"
          ]
        },
        {
          "id": "test-interop-standards",
          "objectiveId": "obj-interop-standards",
          "title": "SCORM, xAPI & the LRS",
          "mcqIds": [
            "lt-mcq-xapi-statement",
            "ot-interop-1",
            "ot-interop-2",
            "ot-interop-3",
            "ot-interop-4",
            "ot-cov-obj-interop-standards-1",
            "ot-cov-obj-interop-standards-2"
          ]
        },
        {
          "id": "test-gamification",
          "objectiveId": "obj-gamification",
          "title": "Gamification & Its Thinkers",
          "mcqIds": [
            "lt-mcq-mechanics",
            "ot-gamification-1",
            "ot-gamification-2",
            "ot-gamification-3",
            "ot-gamification-4"
          ]
        },
        {
          "id": "test-sdt",
          "objectiveId": "obj-sdt",
          "title": "SDT & Intrinsic Motivation",
          "mcqIds": [
            "ot-sdt-1",
            "ot-sdt-2",
            "ot-sdt-3",
            "ot-sdt-4",
            "ot-sdt-5"
          ]
        }
      ]
    },
    {
      "id": "l9-concepts",
      "title": "Who's Who & What's What of Learning",
      "order": 9,
      "studyGuidePath": "/packs/learning-theory/guides/l9-concepts.md",
      "sources": [
        {
          "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
        }
      ],
      "parts": [
        {
          "id": "l9-p1-theorists",
          "title": "The theorists",
          "order": 1,
          "blurb": "Name the thinker behind each big idea, from Pavlov's dogs to Sal Khan's AI tutor.",
          "studyGuideAnchor": "the-theorists",
          "itemIds": [
            "lt-concept-skinner",
            "lt-concept-pavlov",
            "lt-concept-piaget",
            "lt-concept-vygotsky",
            "lt-concept-dewey",
            "lt-concept-bloom",
            "lt-concept-ebbinghaus",
            "lt-concept-csikszentmihalyi",
            "lt-concept-siemens",
            "lt-concept-khan",
            "mcq-rw-l9-p1-theorists",
            "ot-theorists-pavlov-1",
            "ot-theorists-skinner-2",
            "ot-theorists-piaget-3",
            "ot-theorists-vygotsky-4",
            "ot-theorists-dewey-5",
            "ot-measurers-ebbinghaus-1",
            "ot-measurers-csik-2",
            "ot-measurers-siemens-3",
            "ot-measurers-khan-4"
          ]
        },
        {
          "id": "l9-p2-frameworks",
          "title": "The frameworks",
          "order": 2,
          "blurb": "Identify the theory or framework from a few clues — the forgetting curve, flow, ADDIE, and more.",
          "studyGuideAnchor": "the-frameworks",
          "itemIds": [
            "lt-concept-forgetting-curve",
            "lt-concept-zpd",
            "lt-concept-blooms-taxonomy",
            "lt-concept-flow",
            "lt-concept-cognitive-load",
            "lt-concept-dual-coding",
            "lt-concept-connectivism",
            "lt-concept-addie",
            "lt-concept-spaced-repetition",
            "lt-concept-testing-effect",
            "mcq-rw-l9-p2-frameworks",
            "ot-memory-fw-curve-1",
            "ot-memory-fw-spacing-2",
            "ot-memory-fw-zpd-3",
            "ot-memory-fw-testing-4",
            "ot-cog-fw-blooms-1",
            "ot-cog-fw-load-2",
            "ot-cog-fw-flow-3",
            "ot-cog-fw-connectivism-4"
          ]
        },
        {
          "id": "l9-p3-right-or-wrong",
          "title": "Right or Wrong: spot the better practice",
          "order": 3,
          "blurb": "Two images, one prompt — pick the approach the evidence actually supports.",
          "itemIds": [
            "lt-cmp-passive-active",
            "lt-cmp-direct-socratic",
            "lt-cmp-formative-summative",
            "lt-cmp-intrinsic-extrinsic",
            "mcq-rw-l9-p3-right-or-wrong"
          ]
        }
      ],
      "objectives": [
        {
          "id": "obj-behaviorist-constructivist-theorists",
          "statement": "Recognize the behaviorist and constructivist theorists (Skinner, Pavlov, Piaget, Vygotsky, Dewey) from their ideas.",
          "demonstrationIds": [
            "d-behaviorists-people",
            "d-constructivists-people"
          ]
        },
        {
          "id": "obj-measurers-moderns",
          "statement": "Recognize the memory researchers and modern figures (Ebbinghaus, Bloom, Csikszentmihalyi, Siemens, Khan), including Bloom's 1984 tutoring finding.",
          "demonstrationIds": [
            "d-measurers",
            "d-modern-figures"
          ]
        },
        {
          "id": "obj-memory-frameworks",
          "statement": "Recognize the memory frameworks — Forgetting Curve, Spaced Repetition, Testing Effect, ZPD — and the most durable study strategy.",
          "demonstrationIds": [
            "d-memory-frameworks",
            "d-testing-effect-practice"
          ]
        },
        {
          "id": "obj-cognitive-id-frameworks",
          "statement": "Recognize the cognitive and instructional-design frameworks (Bloom's Taxonomy, Flow, Cognitive Load, Dual Coding, Connectivism, ADDIE).",
          "demonstrationIds": [
            "d-cognitive-frameworks",
            "d-id-frameworks"
          ]
        }
      ],
      "demonstrations": [
        {
          "id": "d-behaviorists-people",
          "label": "Behaviorists",
          "itemIds": [
            "lt-concept-skinner",
            "lt-concept-pavlov"
          ]
        },
        {
          "id": "d-constructivists-people",
          "label": "Constructivists",
          "itemIds": [
            "lt-concept-piaget",
            "lt-concept-vygotsky",
            "lt-concept-dewey"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-measurers",
          "label": "Measurers",
          "itemIds": [
            "lt-concept-ebbinghaus",
            "lt-concept-bloom",
            "lt-concept-csikszentmihalyi"
          ],
          "requiredCorrect": 2
        },
        {
          "id": "d-modern-figures",
          "label": "Modern figures",
          "itemIds": [
            "lt-concept-siemens",
            "lt-concept-khan",
            "mcq-rw-l9-p1-theorists"
          ]
        },
        {
          "id": "d-memory-frameworks",
          "label": "Memory frameworks",
          "itemIds": [
            "lt-concept-forgetting-curve",
            "lt-concept-spaced-repetition",
            "lt-concept-testing-effect",
            "lt-concept-zpd"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-testing-effect-practice",
          "label": "Testing effect in practice",
          "itemIds": [
            "lt-concept-testing-effect",
            "mcq-rw-l9-p3-right-or-wrong"
          ]
        },
        {
          "id": "d-cognitive-frameworks",
          "label": "Cognitive frameworks",
          "itemIds": [
            "lt-concept-blooms-taxonomy",
            "lt-concept-flow",
            "lt-concept-cognitive-load",
            "lt-concept-dual-coding"
          ],
          "requiredCorrect": 3
        },
        {
          "id": "d-id-frameworks",
          "label": "ID frameworks",
          "itemIds": [
            "lt-concept-connectivism",
            "lt-concept-addie",
            "mcq-rw-l9-p2-frameworks"
          ]
        }
      ],
      "objectiveTests": [
        {
          "id": "test-behaviorist-constructivist-theorists",
          "objectiveId": "obj-behaviorist-constructivist-theorists",
          "title": "Behaviorists & Constructivists",
          "mcqIds": [
            "ot-theorists-pavlov-1",
            "ot-theorists-skinner-2",
            "ot-theorists-piaget-3",
            "ot-theorists-vygotsky-4",
            "ot-theorists-dewey-5"
          ]
        },
        {
          "id": "test-measurers-moderns",
          "objectiveId": "obj-measurers-moderns",
          "title": "Measurers & Modern Figures",
          "mcqIds": [
            "mcq-rw-l9-p1-theorists",
            "ot-measurers-ebbinghaus-1",
            "ot-measurers-csik-2",
            "ot-measurers-siemens-3",
            "ot-measurers-khan-4"
          ]
        },
        {
          "id": "test-memory-frameworks",
          "objectiveId": "obj-memory-frameworks",
          "title": "Memory Frameworks",
          "mcqIds": [
            "mcq-rw-l9-p3-right-or-wrong",
            "ot-memory-fw-curve-1",
            "ot-memory-fw-spacing-2",
            "ot-memory-fw-zpd-3",
            "ot-memory-fw-testing-4"
          ]
        },
        {
          "id": "test-cognitive-id-frameworks",
          "objectiveId": "obj-cognitive-id-frameworks",
          "title": "Cognitive & Design Frameworks",
          "mcqIds": [
            "mcq-rw-l9-p2-frameworks",
            "ot-cog-fw-blooms-1",
            "ot-cog-fw-load-2",
            "ot-cog-fw-flow-3",
            "ot-cog-fw-connectivism-4"
          ]
        }
      ]
    },
    {
      "id": "l10-vocabulary",
      "title": "Essential Vocabulary & Quick Recall",
      "order": 10,
      "studyGuidePath": "/packs/learning-theory/guides/l10-p1-ai-adaptive.md",
      "sources": [
        {
          "label": "Education Theory & Learning Technology — research compilation (Perplexity)"
        }
      ],
      "parts": [
        {
          "id": "l10-p1-ai-adaptive",
          "title": "AI & adaptive-systems terms",
          "order": 1,
          "blurb": "The core of intelligent tutors: adaptive systems, knowledge tracing, and the agents and models that drive them.",
          "studyGuideAnchor": "ai-adaptive-systems-terms",
          "itemIds": [
            "lt-def-als",
            "lt-def-its",
            "lt-def-cognitive-tutor",
            "lt-def-knowledge-state",
            "lt-def-bkt",
            "lt-def-dkt",
            "lt-def-algorithm-sequencing",
            "lt-cmp-bkt-dkt",
            "mcq-rw-l10-p1-ai-adaptive",
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          "id": "l10-p3-assessment-data",
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            "lt-def-personalized-learning",
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            "lt-def-scaffolded-curriculum"
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        {
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            "lt-def-kirkpatrick",
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            "lt-def-syllabus"
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          "requiredCorrect": 3
        }
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      "objectiveTests": [
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          "mcqIds": [
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            "ot-adaptive-knowledge-state",
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        {
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            "ot-ls-not-accurate",
            "ot-ls-pck"
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        },
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            "mcq-rw-l10-p3-assessment-data",
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            "ot-assess-xapi",
            "ot-assess-learner-analytics",
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    }
  ]
}