Concept

SuperMemo 2 (SM-2) Algorithm

The SuperMemo 2 (SM-2) algorithm calculates intervals for spaced repetition learning. The steps are:

  1. Split knowledge into distinct items.
  2. Initialize E-Factor (easiness of memorizing) to 2.5 for all items.
  3. Repeat items using the following intervals in days, where I(n)I(n) is the interval after the nn-th repetition:
  • I(1):=1I(1) := 1
  • I(2):=6I(2) := 6
  • For n>2n > 2: I(n):=I(n1)×EFI(n) := I(n-1) \times EF
  1. Assess the quality of the response (qq) on a 0-5 scale: 5 (perfect), 4 (correct after hesitation), 3 (correct but difficult), 2 (incorrect, but correct answer seemed easy to recall), 1 (incorrect, but correct answer remembered), 0 (complete blackout).
  2. Update the E-Factor using the formula: EFnew:=EF+(0.1(5q)×(0.08+(5q)×0.02))EF_{new} := EF + (0.1 - (5-q) \times (0.08 + (5-q) \times 0.02)). If EFnew<1.3EF_{new} < 1.3, set EFnew=1.3EF_{new} = 1.3.
  3. If q<3q < 3, repeat the item without changing the E-Factor.
  4. Repeat the session until a grade of at least q=4q = 4 is achieved for all items.

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Updated 2026-06-15

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Data Science