Marginal Utility Mapping
Updated 2026-09-11
INTRODUCTION
English translation pending.
CORE DEFINITION
Marginal utility mapping estimates how much additional skill or understanding another hour of study would yield in each competing topic, then allocates learning time accordingly. Its core proposition is that study hours are scarce and each topic carries a different marginal return, so the learner should rank topics by their next-hour payoff rather than by habit or by equal shares. The key condition is that the estimate must be revised as mastery grows.
SCAFFOLDING EFFECT
Reduce cognitive load
- Rank by next hour: compare topics by what one more hour would actually yield. - Reallocate the time: move hours away from well-mastered topics toward high-return weak spots. - Rebalance over time: update the map as each topic's marginal return falls.
Anchor fast decisions
The return on one more hour differs sharply between topics. A topic already mastered yields little, while a weak high-value topic yields much, so mapping those marginal rates lets a fixed budget of time buy the most learning it can.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Marginal_utilityverified
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