SuperMemo algorithm
Here are some terms that we will deal with when impementing the SuperMemo (SM-2) algorithm of spaced repetition.
- repetitions - this is the number of times a user sees a flashcard.
0
means they haven't studied it yet, 1
means it is their first time, and so on. It is also referred to as n
in some of the documentation.
- quality - also known as quality of assessment. This is how difficult (as defined by the user) a flashcard is. The scale is from
0
to 5
.
- easiness - this is also referred to as the easiness factor or EFactor or EF. It is multiplier used to increase the "space" in spaced repetition. The range is from
1.3
to 2.5
.
- interval - this is the length of time (in days) between repetitions. It is the "space" of spaced repetition.
- nextPractice - This is the date/time of when the flashcard comes due to review again.
Default values
int repetitions = 0;
int interval = 1;
float easiness = 2.5;
Code
I found this Python implementation somewhat easier to follow than the SuperMemo example source code, so I am more or less following that.
private void calculateSuperMemo2Algorithm(FlashCard card, int quality) {
if (quality < 0 || quality > 5) {
// throw error here or ensure elsewhere that quality is always within 0-5
}
// retrieve the stored values (default values if new cards)
int repetitions = card.getRepetitions();
float easiness = card.getEasinessFactor();
int interval = card.getInterval();
// easiness factor
easiness = (float) Math.max(1.3, easiness + 0.1 - (5.0 - quality) * (0.08 + (5.0 - quality) * 0.02));
// repetitions
if (quality < 3) {
repetitions = 0;
} else {
repetitions += 1;
}
// interval
if (repetitions <= 1) {
interval = 1;
} else if (repetitions == 2) {
interval = 6;
} else {
interval = Math.round(interval * easiness);
}
// next practice
int millisecondsInDay = 60 * 60 * 24 * 1000;
long now = System.currentTimeMillis();
long nextPracticeDate = now + millisecondsInDay*interval;
// Store the nextPracticeDate in the database
// ...
}
Notes
- The code above does not set an upper limit on
easiness
. Should it be 2.5
? The documentation and source code seemed to contradict each other.
- The documentation also made it sound like the easiness factor should not be updated if the quality assessment was less than 3, but this seems to contradict the source code. It also seems to me to make more sense to update it (as long as it is kept above 1.3). Anyway, I am updating it every time.
- The Anki source code is here. It is a big project, though, and I haven't dug down deep enough yet to see their version of the algorithm.
- This post talks about some problems with SM-2 and solutions for those problems.
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