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references/knowledge/metacognition.md
2.59 KB · Oct 5, 2026 · 18:32 UTC
<!-- Generated from skills/metacognition/SKILL.md; edit the canonical source. --> # Metacognition **Evidence tier: strong.** Confidence-calibration and self-monitoring research (Koriat 1997; Flavell 1979) is well-replicated; metacognitive-strategy instruction shows consistent positive effects. ## Teaching Learners HOW to Learn - **Prediction**: Before attempting a problem, ask "How hard do you think this will be?" - **Monitoring**: During work, ask "What is your strategy right now?" - **Evaluation**: After completing, ask "What was harder than expected? What was easier?" - **Self-assessment calibration**: "How confident are you in this answer, 1-10?" Then compare to actual result. ## Per-Item Confidence Tagging (Koriat) The cheapest high-value calibration intervention: before an answer is judged, the learner tags it `sure` / `mostly` / `guessing`. The order is load-bearing — confidence stated **after** the reveal measures hindsight, not monitoring (Koriat, *Monitoring one's own knowledge during study*, 1997). Over time the tags expose the two patterns that matter: - **Overconfidence** (`sure` + incorrect): the illusion-of-competence signature. These concepts need retrieval practice, not re-reading. - **Underconfidence** (`guessing` + correct): knowledge is present but not trusted; name it to the learner — confidence calibration cuts both ways. `quiz` skill collects the tag with every answer; tags land in `reviewHistory[].confidence` (see `state-schema` KB) and `bodhi-state calibration` aggregates them for `progress` skill and `reflect` skill. Never scold a miscalibrated tag — the honest tag IS the rep. The `predictionDelta` block in `assessment-history.json` is the same mechanism at journey scale (`evaluate` skill Phase 2.5: predict-before-reveal). ## The Dunning-Kruger Effect in Programming Beginners overestimate their skills because they lack the knowledge to assess what they do not know. This is not arrogance — it is a genuine cognitive limitation. The antidote is calibrated self-assessment through repeated prediction-and-check cycles. ## Illusions of Competence (Oakley) Watch for these dangerous patterns: - **Passive rereading**: Moving eyes over text without recall - **Glancing at solutions**: Looking at a worked solution and thinking "I get it" without reproducing it - **Recognition vs recall**: "This looks familiar" is NOT the same as "I can produce this from memory" - **The Einstellung effect**: An existing idea blocks finding a better solution Antidote: Always test with retrieval. If the learner says "I understand," ask them to prove it by explaining or solving from scratch.
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