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Learning β

Forgetting curve



The forgetting curve is a curve that describes how people's knowledge of a fact, or understanding of a concept, decays with time after they last reviewed it. The typical model for a forgetting curve is exponential decay. Ebbinghaus suggested the model:

R = R_0e^{-t/S}

where R_0 is the initial recall level, t is the time since initial recall, and S is the strength of memory (higher S means slower decay, more time means more decay, and higher R_0 means a better starting point, so the decay is lagged).

Related strategies

Strategies to combat forgetting

  • Spaced repetition is an approach where material is reviewed at strategic time intervals so as to increase the strength of recall as much as possible. The general idea is to space out the intervals for reviewing the material with the gap between successive review intervals growing exponentially.
  • Deep learning is an approach to learning that emphasizes learning in a manner that maximizes the degree to which the material is internalized by drawing deep connections with related ideas. It is believed that deep learning facilitates higher strength of memory (S) and hence slower forgetting.
  • Overlearning is a strategy where people learn something beyond the point of initial mastery with the goal of attaining automaticity. This may delay forgetting either through increasing R_0 or through increasing S.

Strategies that encourage or fail to combat forgetting

  • Cramming is a strategy whereby one reviews a large chunk of material shortly before one is to be tested on it. This strategy is very non-optimal for learning. Note that cramming is opposed to spaced repetition (because there is only one point in time for reviewing the material), deep learning (because reviewing a lot of material at once is not conducive to understanding it deeply), and overlearning (because it is not possible to do sufficient practice to attain automaticity if one is reviewing a lot of material all together)