Spaced repetition

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Spaced repetition is a learning technique in which increasing intervals of time are used between subsequent reviews. Alternative names include expanding rehearsal, graduated intervals^{[citation needed]}, repetition spacing, repetition scheduling, spaced retrieval and expanded retrieval.

Contents 1 Applications 2 Prominent researchers 3 Software 4 See also 5 References

[edit] Applications

Practical applications of spaced repetition were first suggested in the book Psychology of Study by Prof. C. A. Mace in 1932.

Pimsleur language courses use spaced repetition techniques, and in the 1970s Sebastian Leitner devised his Leitner system, an all-purpose system based on flashcards.

More recently, spaced repetition has also been implemented into computer-assisted language learning software^{[citation needed]} to gradually adapt the optimum spacing of repetitions to individual needs. A typical optimization criterion used in spaced repetition is the requested level of knowledge retention, i.e. percent of knowledge that is to be remembered.

There are several families of algorithms for scheduling spaced repetition:

• Neural networks based
• Sebastian Leitner system learning machines:
  • 5 stages
  • n stages
• SM-family of algorithms (SuperMemo):
  • SM-0
  • SM-2
  • SM-4
  • SM-5
  • SM-6
  • SM-8
  • SM-11

The precise length of intervals does not have a great impact on algorithm effectiveness, as reflected in data collected by Mnemosyne.^[1]

[edit] Prominent researchers

• Cecil Alec Mace
• Hermann Ebbinghaus
• Paul Pimsleur
• Sebastian Leitner

[edit] Software

• Anki
• Mnemosyne (spaced repetition software)
• Parley (KDE) - successor to KVocTrain (KDE3), adds spaced recognition support
• SuperMemo
• VTrain
• Winflash

[edit] See also

• Study Software
• Testing effect
• Spacing effect
• Graduated interval recall (System developed by Paul Pimsleur)

[edit] References