── ── Strategy
Metacognition
Metacognition is the live monitoring loop during reasoning — "am I doing this right now; what strategy am I using; should I switch?" — not after-the-fact reflection. Coined by Flavell (1979); operationalized by Pólya's 1945 four-stage protocol; empirically validated by Schoenfeld (1985): experts spend 30–40% of problem-solving time monitoring; novices spend 5%. The expert-novice gap is less raw knowledge than…
How it works
Run Pólya's Four-Stage Protocol with Explicit Monitoring (Pólya 1945 + Schoenfeld 1985).
1. Understand (with monitoring). Restate the problem in your own words; identify unknowns, data, constraints. Ask: "Do I genuinely understand this, or just recognize the topic?" 2. Devise a plan (with monitoring). Choose a strategy. Ask: "Why this strategy?" — if you can't articulate it, you're pattern-matching. Set a time-budget: "I'll give this 20 minutes." 3. Carry out the plan (with monitoring). Execute. At each step: "Is this advancing me, or just generating motion?" Set re-evaluation triggers (every N minutes, every dead end). 4. Look back (with monitoring). Did it work? Why? What was the moment to have switched? Record the meta-lesson, not just the solution. 5. Recognize the stuck-loop. 30+ minutes cycling with no progress → restate to someone else (rubber-duck), give up your current framing, or take a real break. 6. Calibrate confidence explicitly. After any conclusion: "How confident, 0–100? What would change this?" 7. Pre-commit re-monitoring schedule. For work longer than a day: "I will re-monitor at days 3, 7, 14."
When to use it
- user says 'I'm stuck and don't know why', 'I keep making the same mistake', 'my analysis feels right but I'm not sure', 'am I solving the right problem', 'I should understand this but I don't', or asks about calibration / thinking about thinking
When not to use it
When the decision is routine and reversible, applying a formal method costs more than it returns.
Worked example
Pólya at Stanford and Schoenfeld at Berkeley (1942 → 1985)
A worked example. Not folklore — university teaching records and peer-reviewed experimental data.
Install this skill (free, MIT)
npx skills add deciqAI/knowledge-skills