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File:Ankireview.png

Anki, a computer program implementing spaced repetition.

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

Although the principle is useful in many contexts, spaced repetition is commonly applied in contexts in which a learner must acquire a large number of items and retain them indefinitely in memory. It is therefore well suited for the problem of vocabulary acquisition in the course of second language learning, due to the size of the target language's inventory of open-class words.

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 sixth-grade students in Iowa learning 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, including Melton[3] and Landauer & Bjork,[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 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.[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 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,[6][7] 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.[8]

Pimsleur's graduated-interval recall[]

Graduated-interval recall is a type of spaced repetition published by Paul Pimsleur in 1967.[9] It is used in the Pimsleur language learning system and is particularly suited to programmed audio instruction due to the very short times (measured in seconds or minutes) between the first few repetitions, as compared to other forms of spaced repetition which may not require such precise timings.

The intervals published in Pimsleur's paper were: 5 seconds, 25 seconds, 2 minutes, 10 minutes, 1 hour, 5 hours, 1 day, 5 days, 25 days, 4 months, and 2 years.

By timing a Pimsleur language program with a stopwatch,[original research?]

it is possible to verify that the intervals are not followed exactly but have upper and lower bounds.  A similar principle (graduated intervals with upper and lower bounds) is used in at least one open source software project (Gradint) to schedule audio-only lessons.  (Another open source project, PimSched, keeps Pimsleur's intervals rigidly, without adding upper or lower bounds.  PimSched currently uses only the first 4 intervals.)

Prominent researchers[]

Prominent practitioners[]

Software[]

Most programs are modeled after the manual style of learning with flashcards: items to memorize are entered into the program as question-answer pairs. When a pair is due to be reviewed, the question is displayed on screen, and the user must attempt to answer. After answering, the user manually reveals the answer and then tells the program (subjectively) how difficult answering was. The program schedules pairs based on spaced repetition algorithms. Without a program, the user has to schedule flashcards; this is time-intensive and limits users to simple algorithms like the Leitner system.

Further refinements with regard to software:

  • Questions and/or answers can be a sound-file to train recognition of spoken words.
  • Automatic generation of pairs (e.g. for vocabulary, it is useful to generate three question-pairs: written foreign word, its pronunciation and its meaning—but data only has to be entered once.
  • Additional information retrieved automatically is available, such as example sentences containing a word.
  • Support for advanced input formats such as LaTeX.
  • Use of a portable web platform instead of an installable program.
  • Opportunities to combine spaced repetition with online community functions, e.g. sharing courses.

Some implementations:

  • Anki
  • eSpindle Learning aka LearnThat.org
  • Flashcard Exchange
  • Course Hero
  • Mnemosyne
  • Skritter
  • SuperMemo
  • Winflash
  • OpenCards

The above list is not comprehensive, nor does it intend to be. The list of flashcard software provides a broader overview.

See also[]

References[]

  1. "Human Memory: Theory and Practice", Alan D. Baddeley, 1997
  2. Spitzer, H. F. (1939). Studies in retention. Journal of Educational Psychology, 30, 641–657.
  3. Melton, A. W. (1970). The situation with respect to the spacing of repetitions and memory. Journal of Verbal Learning and Verbal Behavior, 9, 596–606.
  4. Landauer, T. K., & Bjork, R. A. (1978). Optimum rehearsal patterns and name learning. In M. Gruneberg, P. E. Morris, & R. N. Sykes (Eds.), Practical aspects of memory (pp. 625–632). London: Academic Press.
  5. See #Software
  6. Cull, W. L. (2000). Untangling the benefits of multiple study opportunities and repeated testing for cued recall. Applied Cognitive Psychology, 14, 215–235.
  7. Peter Bienstman on Mnemosyne mailing list, May 2008
  8. Chapter 6:Is Expanded Retrieval Practice a Superior Form of Spaced Retrieval?, A Critical Review of the Extant Literature, DAVID A. BALOTA, JANET M DUCHEK, and JESSICA M. LOGAN
  9. Pimsleur, Paul (February 1967). A Memory Schedule 51 (2): 73–75.

Further reading[]

  • Caple, C. (1996). "The Effects of Spaced Practice and Spaced Review on Recall and Retention Using Computer Assisted Instruction". Dissertation for the degree of Doctor of Education, North Carolina State University.[1]
  • de Boer, V. (2003, August). "Optimal Learning and the Spacing Effect: Theory, Application and Experiments based on the Memory Chain Model". Artificial Intelligence Master's Thesis for Computational Psychology, University of Amsterdam.[2]
  • Dempster, F. N. (1988). "The Spacing Effect: A Case Study in the Failure to Apply the Results of Psychological Research". American Psychologist, 43(8), 627-634.
  • Greene R. L. (2008). Repetition and spacing effects. In Roediger H. L. III (Ed.), Learning and memory: A comprehensive reference. Vol. 2: Cognitive psychology of memory (pp. 65–78). Oxford: Elsevier.
  • Karpicke, J. D., & Roediger, H. L. (2007). "Expanding Retrieval Practice Promotes Short-Term Retention, but Equally Spaced Retrieval Enhances Long-Term Retention". Journal of Experimental Psychology: Learning, * Memory, and Cognition, 33(4), 704-719.[3]
  • (2007). Randomized, Controlled Trial of Spaced Education to Urology Residents in the United States and Canada. The Journal of Urology 177 (4): 1481–1487.
  • Pavlik, P. I. (2005). The Microeconomics of Learning: Optimizing Paired-Associate Memory. PhD, Carnegie Mellon.
  • (2008). Using a model to compute the optimal schedule of practice. Journal of Experimental Psychology 14 (2): 101–117.




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