The Bottom Line
- Prospective calendars measure intention, not retention.
- A tracker using Last Reviewed + Accuracy + Confidence drives efficient targeting.
- Use Red/Amber/Green status to prioritise like clinical risk stratification.
The Concept
Standard timetables fail because forgetting is not linear and life is not predictable. A retrospective system measures what you have actually mastered and when it was last tested. That turns revision into a feedback loop: monitor performance → update priorities → retest. In cognitive science terms, you are operationalising self-regulated learning with minimal friction. The result: fewer wasted hours revisiting strong topics, and faster movement of weak topics into stable recall.
Scientific Evidence
Self-regulated learning models emphasise monitoring, metacognitive judgement, and strategy adjustment based on performance data. A retrospective tracker formalises this into a repeatable workflow.
Implementation Strategy
1
Phase 1: Build a simple spreadsheet
Columns: Topic, Subtopic, Q-bank Source, Last Reviewed (date), Accuracy (%), Confidence (1–3), Status (Red/Amber/Green), Next Due.
2
Phase 2: Define traffic-light rules
Red: Accuracy < 60% OR Confidence=1 OR Last Reviewed > 21 days. Amber: 60–80% OR Confidence=2. Green: >80% AND Confidence=3 AND Last Reviewed < 14 days.
3
Phase 3: Daily prioritisation
Start by filtering Red. Do a short mixed block, then a focused block on the top Red domain. Update Last Reviewed + Accuracy immediately after.
4
Phase 4: Weekly audit
Review the top 10 Reds: decide whether each is a knowledge gap (missing content), technique gap (stem/logic), or state gap (fatigue/anxiety). Choose the correct fix.
Practice
Test your knowledge
Apply this concept immediately with a high-yield question block from the iatroX Q-Bank.
SourceRead the original paper (PubMed)
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