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Retrieval Practice Scheduling

Burn the right things in — at the moment forgetting would happen.

Schedules and presents recall prompts from a fixed item set, grades each attempt, and re-schedules based on the signal so retention compounds over time. Use this when the goal is durable retention of a known body of knowledge — not understanding or certification.

Shape

SPACED-REPETITION CYCLEitem setSchedulerwhen forgetting is duepromptscorenext-duerescheduleretention trace

Operational dimensions

No human in loop

Runs without a person in the path.

Scheduled

Fires on a clock.

Medium data gravity

Holds working state that compounds over runs.

Closed surface

No external systems on either side.

Inputs

  • item set (flashcards, cloze items, procedural cues)
  • learner recall attempt (correct / incorrect / partial)
  • learner's prior recall history per item

Outputs

  • per-item recall trace with timestamp
  • next-due schedule for each item
  • retention estimate per item and aggregate

Mechanism

Drills a learner on a defined item set using spaced-repetition / active-recall scheduling so that retention is the demonstrated outcome.

Why this is a primitive

Cannot be decomposed — the schedule-prompt-score-reschedule cycle over a fixed item set is one operation. It does not instruct (no explanation), route curriculum (no branching across units), or assess for certification (no completion claim).

Where it shows up

Medical school — students drill drug–interaction facts on a spaced schedule before clinical placements
Language-learning app — vocabulary items resurface at the moment forgetting is predicted, not on a fixed daily batch
Compliance platform — employees re-encounter key policy facts quarterly without admin scheduling each session manually

Related primitives

Tags

AIlearningretentionautonomousbatch

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