Feedback Loop & Mastery Climb

Feedback Settings

Feedback delay 0 attempts

Specificity 70%

Feedback type

Practice speed 1.5 / s

Live Readouts

Attempt #

Mastery

12.0%

Est. attempts to 90% mastery at current settings

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How it works

Each practice attempt, the learner's observed score is their current mastery plus noise. Feedback then nudges mastery toward 1 (full mastery), following a simplified version of Hattie & Timperley's (2007) feedback-effectiveness model, in which the size of the nudge depends on three levers:

effect = specificity × typeMult × exp(−delay / 3)
M(n+1) = M(n) + η · effect · (1 − M(n)) − φ · M(n) · (1 − effect)

Delay — feedback given trials later decays exponentially in usefulness (exp(−delay/3)); by ~6 attempts late it is nearly inert, matching the well-replicated finding that immediate feedback drives faster skill gains than delayed feedback.
Specificity — vague feedback ("good job") carries little corrective signal; precise, task-level feedback carries a strong one, scaling the nudge from 0 to 1.
Type — corrective feedback (typeMult = 1.0) points at the actual error and drives learning fastest; pure affirmative praise (typeMult = 0.45) feels good but carries much less corrective information, so mastery climbs more slowly.
Forgetting — when effective feedback is absent (high delay, low specificity), a small forgetting term φ·M·(1−effect) lets mastery slowly decay, so skill isn't ratcheted upward for free.

η = 0.22 (base learning rate), φ = 0.02 (forgetting rate). The mastery marker climbs a spiral staircase whose height directly encodes M(n); the bars behind it are the raw, noisy attempt scores the learner actually produced.

Mastery marker Strong attempt Weak attempt

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Assessment Feedback Simulation