Optimal Memorization
Wired has an excellent article on an optimal memorization algorithm developed by Piotr Wozniak. The technique has been embodied in a software program called SuperMemo and an opensource alternative called Mnemosyne
I’m somewhat skeptical that spending more time on memorizing facts is that useful but given that a few months ago I could barely remember the equation for the roots of a quadratic perhaps I should be more openminded.
The algorithm is straightforward:

 Split the knowledge into smallest possible items.
 With all items associate an EFactor equal to 2.5.
 Repeat items using the following intervals:
I(1):=1
I(2):=6
for n>2: I(n):=I(n1)*EF
where:
I(n) – interrepetition interval after the nth repetition (in days),
EF – EFactor of a given item
If interval is a fraction, round it up to the nearest integer.  After each repetition assess the quality of repetition response in 05 grade scale:
5 – perfect response
4 – correct response after a hesitation
3 – correct response recalled with serious difficulty
2 – incorrect response; where the correct one seemed easy to recall
1 – incorrect response; the correct one remembered
0 – complete blackout.  After each repetition modify the EFactor of the recently repeated item according to the formula:
EF’:=EF+(0.1(5q)*(0.08+(5q)*0.02))
where:
EF’ – new value of the EFactor,
EF – old value of the EFactor,
q – quality of the response in the 05 grade scale.
If EF is less than 1.3 then let EF be 1.3.  If the quality response was lower than 3 then start repetitions for the item from the beginning without changing the EFactor (i.e. use intervals I(1), I(2) etc. as if the item was memorized anew).
 After each repetition session of a given day repeat again all items that scored below four in the quality assessment. Continue the repetitions until all of these items score at least four.
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