# Spaced repetition

**Spaced repetition** is a learning method based on computing optimum intervals that should separate review of individual pieces of knowledge to achieve a desired level retention. SuperMemo pioneered the use of optimization methods in spaced repetition. Over the last two decades, spaced repetition has evolved into incremental reading.

SuperMemo 18 for Windows uses forgetting curves and the two component model of memory to make best optimum interval predictions.

SuperMemo 1.0 for DOS was the first implementation of spaced repetition (1987). SuperMemo celebrated its 30th birthday on Dec 13, 2017.

The method was first described in Piotr Wozniak's Master's Thesis: *Optimization of learning* in 1990, and in a peer review journal in 1994.

Alternative terms used to refer to spaced repetition with approximate period of use in reference to SuperMemo: *SuperMemo method* (1989-1995), *optimum intervalization* (1990-1992), *scheduling repetitions* (1992-1995), *repetition spacing* or *spacing of repetitions* (1992-1999, literature), *graduated intervals* (Pimsleur), *spaced rehearsal* or *expanding rehearsal* (literature, e.g. Landauer & Bjork), *spaced, expanded*, or *expanding retrieval* (literature), *spaced practice*, *expanded practice* or *distributed practice* (literature, e.g. Baddley), *optimum schedule* (literature, e.g. Pavlik), *spaced learning* or *spaced education*, and more. The term *spaced repetition* was adopted by SuperMemo in 1999. For more see: Alternative terms for spaced repetition

As the term **spaced repetition** was loosely used before the birth of SuperMemo, and adopted in the present meaning only in 1999, we may occasionally use the term **computational spaced repetition** to differentiate the SuperMemo method from a review schedule in which intervals increase but are not explicitly computed or optimized.

See also:

- What is spaced repetition? (1990)
- History of spaced repetition (2018)
- Research background (1995)

This glossary entry is used to explain "*History of spaced repetition*" by Piotr Wozniak (June 2018)

Figure:A typical snapshot from an incremental reading process in SuperMemo. While learning about leptin, the student extracts important portions of the text (in blue), and marks keywords that will be used to form questions that will enhance memory in the long term (in dark orange). The questions are reviewed along a spaced repetition schedule. See this video example for an explanation. The brain picture was taken from here

Figure:The first forgetting curve for newly learned knowledge collected with SuperMemo. Power approximation is used in this case due to the heterogeneity of the learning material freshly introduced in the learning process. Lack of separation by memory complexity results in superposition of exponential forgetting with different decay constants. On a semi-log graph, the power regression curve is logarithmic (in yellow), and appearing almost straight. The curve shows that in the presented case recall drops merely to 58% in four years, which can be explained by a high reuse of memorized knowledge in real life. The first optimum interval for review at retrievability of 90% is 3.96 days. The forgetting curve can be described with the formula R=0.9906*power(interval,-0.07), where 0.9906 is the recall after one day, while -0.07 is the decay constant. In this is case, the formula yields 90% recall after 4 days. 80,399 repetition cases were used to plot the presented graph. Steeper drop in recall will occur if the material contains a higher proportion of difficult knowledge (esp. poorly formulated knowledge), or in new students with lesser mnemonic skills. Curve irregularity at intervals 15-20 comes from a smaller sample of repetitions (later interval categories on a log scale encompass a wider range of intervals)

Figure:Changes in memory status over time for an exemplary piece of knowledge. The horizontal axis represents time spanning the entire repetition history. The top panel shows retrievability (tenth power, R^{10}, for easier analysis). Retrievability grid in gray is labelled by R=99%, R=98%, etc. The middle panel displays optimum intervals in navy. Repetition dates are marked by blue vertical lines and labelled in aqua. The end of the optimum interval where R crosses 90% line is marked by red vertical lines (only if intervals are longer than optimum intervals). The bottom panel visualizes stability (presented as`ln(S)/ln(days)`

for easier analysis). The graph shows that retrievability drops fast (exponentially) after early repetitions when stability is low, however, it only drops from 100% to 94% in long 10 years after the 7th review. All values are derived from an actual repetition history and the three component model of memory.