Spaced Repetition - Research and Applications

Research and Applications

The notion that spaced repetition could be used for improving learning was first 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 sixth-grade students in Iowa learning science facts. 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, including Melton and Landauer & Bjork, 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 implemented via flashcard systems. These systems were unwieldy because any significant study base requires many thousands of flashcards. With the increase in access to personal computers in the 1980s, spaced repetition began to be implemented with computer-assisted language learning software-based solutions. The aim of these programs was to tailor the spaced repetition to learner performance. 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 appears more often and material that is easy less often, with difficulty defined according to 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
• Leitner system: 5 stages and an arbitrary number of stages
• SM-family of algorithms (SuperMemo): SM-0 (a paper implementation) to SM-11 (in SuperMemo 2006)

Some have theorized that the precise length of intervals does not have a great impact on algorithm effectiveness, although it has been suggested by others that the interval (expanded vs. fixed interval, etc.) is quite important; the experimental data regarding this point are mixed.