Spaced Practice Schedule Builder
Design a spaced retrieval schedule for any topic list and timeline. Use when planning units, term sequences, or revision programmes.
What it does
Takes a list of topics and a teaching timeline and generates an optimised review schedule that spaces retrieval opportunities at expanding intervals to combat the forgetting curve. The output is a week-by-week plan showing when to introduce new content and when to revisit previous topics, with specific activity suggestions for each review slot. AI is specifically valuable here because calculating optimal spacing intervals across multiple topics while respecting prerequisite dependencies and timetable constraints is genuinely complex — most teachers default to blocked practice (finish topic A, move to topic B, never return) because the cognitive load of planning spaced schedules manually is too high.
The evidence behind it
Ebbinghaus (1885/1913) first demonstrated that memory follows an exponential decay curve — without review, approximately 70% of new learning is lost within 24 hours. Cepeda et al. (2006) conducted a meta-analysis of 254 studies and established that the optimal gap between study sessions depends on the desired retention interval: roughly 10–20% of the retention interval is optimal (e.g., if you need students to remember something for 30 days, space reviews approximately 3–6 days apart). Carpenter et al. (2012) extended these findings to diverse classroom learning contexts, showing that spaced practice benefits declarative knowledge, procedural skills, and problem-solving. Kornell & Bjork (2008) demonstrated that spacing feels less effective to learners — students rate massed practice as more effective even when spaced practice produces better retention. This means teachers should expect students to initially prefer (and request) the less effective approach. Dunlosky et al. (2013) rated distributed practice as one of only two "high utility" strategies in their comprehensive review.
Sources
- Ebbinghaus (1885/1913) — The forgetting curve: exponential decay of memory without review
- Cepeda et al. (2006) — Meta-analysis of 254 studies on distributed practice: optimal spacing depends on retention interval
- Kornell & Bjork (2008) — Spacing and interleaving effects on learning
- Carpenter et al. (2012) — Using spacing to enhance diverse forms of learning
- Dunlosky et al. (2013) — Distributed practice rated high-utility learning strategy
How to use it in your lesson
For the best results with EvidenceLesson, give it:
- topics — List of topics or concepts to be spaced across the schedule
- timeline — Available teaching period (e.g. '6-week half-term' or 'Term 2: Jan 15 – Mar 28')
- lessons_per_week — Number of lessons per week for this subject
- assessment_date (optional) — Date of summative assessment, if known — affects final spacing intervals
- topic_difficulty (optional) — Teacher's estimate of relative difficulty for each topic (high/medium/low)
- curriculum_sequence (optional) — From context engine: mandated teaching order or prerequisite dependencies
- student_profiles (optional) — From context engine: class-level retention data from prior assessments
Known limitations
- The schedule assumes relatively even topic length. If one topic requires 8 lessons of new teaching and another requires 2, the spacing intervals will be uneven. Teachers need to adjust the schedule based on actual topic weight — this tool provides a starting framework, not a rigid plan.
- Optimal spacing intervals from Cepeda et al. (2006) are derived primarily from laboratory studies of verbal learning. Transfer to complex procedural skills (e.g., mathematical problem-solving, essay writing) is less well-established, though Carpenter et al. (2012) provide supportive classroom evidence.
- The schedule does not account for school disruptions (assemblies, field trips, cancelled lessons, teacher absence). Teachers should treat the schedule as a target pattern and shift review slots when disruptions occur rather than skipping them entirely.