Spaced repetition

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Spaced repetition is a learning technique that incorporates increasing intervals of time between subsequent review of previously learned material; this exploits the psychological spacing effect. Alternative names include spaced rehearsal, expanding rehearsal, graduated intervals, repetition spacing, repetition scheduling, spaced retrieval and expanded retrieval [1].


Research and Applications

The notion that spaced repetition could be used for improving learning was first[citation needed] proposed in the book Psychology of Study by Prof. C. A. Mace in 1932. In 1939, Spitzer tested the effects of a type of spaced repetition on 6th Graders in Iowa to learn science facts [2]. Spitzer tested over 3600 students in Iowa and showed that spaced repetition was effective. This early work went unnoticed and the field was relatively quiet until the late 1960s when cognitive psychologists, notably including Landuaer & Bjork[3] and Melton[4], explored manipulation of repetition timing as a means to improve recall. Around the same time, Pimsleur language courses pioneered the practical application of spaced repetition theory to language learning and in 1973, Sebastian Leitner devised his "Leitner system", an all-purpose spaced repetition learning system based on flashcards.

At the time, spaced repetition learning was principally being implemented via flashcard systems; these systems were somewhat unwieldy since any significant study base requires many thousands of flashcards. With the increase in accessibility of personal computing, spaced repetition began to be implemented with computer-assisted language learning software-based solutions in the 1980s. The aim of these programs was to tailor the repetition spacing based on learner performance [5]. To enable the user to reach a target level of achievement (e.g. 90% of all material correctly recalled at any given time point), the software adjusts the repetition spacing interval. Material that is hard is shown more often and material that is easy is shown less often, with hard or easy being defined by the ease with which the user is able to produce a correct response.

There are several families of algorithms for scheduling spaced repetition:

  • Neural networks based
  • Sebastian Leitner system learning machines: 5 stages and an arbitrary number of stages
  • SM-family of algorithms (SuperMemo): SM-0 (a paper implementation) to SM-11 (in SuperMemo 2006)

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