Individual Spacing Algorithm Explainer

What This Skill Does

Generates a personalised spaced repetition schedule for a specific set of knowledge items based on student performance data, and explains the algorithm logic in teacher-friendly terms. This skill does NOT execute the spacing algorithm, execution requires a system like Anki, Quizlet, SuperMemo, or Kaku's own retention engine. What this skill does is DESIGN and EXPLAIN: given what students know and what they're forgetting, it produces a concrete review schedule with clear rationale for why each interval was chosen. The core insight from spacing research is that the optimal review interval depends on the desired retention period and the item's current memory strength. Ebbinghaus (1885) established that forgetting follows a predictable curve, steep initially, then gradually flattening. Cepeda et al. (2006) demonstrated in a comprehensive meta-analysis that spacing review across time produces substantially better long-term retention than massing the same amount of practice into a single session. The practical challenge is that the optimal interval is different for every student and every item, which is where personalisation becomes essential. AI is specifically valuable here because calculating optimal intervals across dozens of items for individual students is computationally trivial for a machine but practically impossible for a teacher doing it manually.

Evidence Foundation