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How SuperMemo aids learning

Once you learn a fact, you need to refresh your memory shortly before forgetting takes place. However, it may be very difficult to predict the moment of forgetting. Some facts are forgotten faster, other can stay in your memory for years. Luckily, there are some regularities in the process of forgetting that can help you optimize the timing of repetitions. Once you learn a collection of new pieces of knowledge, let us call these pieces items, you can observe a slow but regular decline in the proportion of items you remember. If you employ the computer to plot the forgetting curve, you can easily predict when a given proportion of items will be forgotten. If you decide to constantly remember at least 90% of the material, you might try to schedule your repetitions at the point when you still remember 90% of what you have learned. It is known that you will still remember most of the material after a much longer period of time. The process of forgetting is random in nature, and you cannot easily say which item will last longer and which will be forgotten sooner. The picture becomes more complicated if you realize that different items have different difficulty and require different inter-repetition intervals. Moreover, items that have already been repeated once or twice, need much less refreshing than those that have just been learned.

There has been a lot of effort put into finding out the regularities in the process of learning. As a result, effective algorithms have been developed that are able to quickly determine the best possible interval for an item independent of its difficulty and the number of earlier repetitions. Those algorithms have been implemented as a computer program known as SuperMemo (available for Windows, on-line access, PDA devices cellulars, etc.). SuperMemo can supervise your repetitions without much involvement on your part. SuperMemo is not painless, because it does not allow you to learn with no effort at all. However, it can be shown in strictly scientific terms that SuperMemo helps you increase the speed of learning many times. Indeed, it makes it possible to approach the maximum natural capacity of the human brain to store and retain information. In theory, over a period of an average lifetime, SuperMemo makes it possible to learn 10-50 times faster than conventional methods, and makes it possible to reach knowledge retention of 95% or more! SuperMemo minimizes the effects of forgetting and the overall time needed for learning. This is done by scheduling repetitions in carefully determined intervals of time called optimum intervals. These optimum intervals are calculated on the basis of two contradictory criteria:

Intervals should be as long as possible to obtain the minimum frequency of repetitions, and to make the best use of the so-called spacing effect, which says that longer inter-repetition intervals, up to a certain limit, produce stronger memories
Intervals should be short enough to ensure that the knowledge is still rememberedt

In practice, these two criteria translate into the following one:Intervals should be as long as it is necessary for a selected small proportion of knowledge be forgotten. This proportion (called the forgetting index) can vary from 3% (for slower and very exact learning) to 20% (for faster learning characterized by a low retention of knowledge).

If the forgetting index drops below 3%, the knowledge acquisition rate becomes unacceptably low. On the other hand, the acquisition rate peaks at the forgetting index of about 20%. Above that value, both the retention and acquisition rate decrease. Note, that one can compare traditional learning, in which repetitions are arbitrarily set in time, to optimized learning with the forgetting index well above 50%. Such learning is not only slow, but above all, the retention of knowledge may be unacceptably low. In consequence, instead of remembering things which are important, you only remember things which are easy to remember or those that receive per-chance repetition while reviewing other parts of the material. As optimum intervals differ for different pieces of knowledge, SuperMemo requires that the learned material be split into smallest possible pieces called items. If items were to be repeated collectively, e.g., as chapters of a textbook in traditional learning, the overall optimal intervals would have to be as short as the optimal intervals for the most difficult subitem in the set. This would make learning even less effective than learning by means of classical methods! Splitting knowledge into small pieces makes it possible for SuperMemo to determine optimum intervals for each item independently. Simplicity of items is perhaps even more important for cytophysiological reasons. Simple items make it possible for the right neuronal synapses to be fully stimulated at the right time. Complex items result in trains of diversified nervous impulses that result in unpredictably intricate memory patterns at the cellular level. This makes optimization of learning difficult or not possible at all. Using optimum intervals and the simplicity of items are a formula for high speed and high retention in learning. However, the speed of learning is not the most important element of education. It is the quality of knowledge that counts most.


With synchronisation, you can move your learning process among the platforms that you access your course from.SuperMemo makes it possible to learn on any platform that you choose:

The key to effective learning is in minimizing the number of repetitions necessary to retain knowledge in memory
SuperMemo minimizes the learning time by approximating optimum intervals (i.e. intervals that should separate individual repetitions)
Knowledge memorized with SuperMemo must be split into smallest possible pieces called items
When using SuperMemo, you must not forget that the quality of learning will depend on the selection of the material, and the way it is split into individual items.

For more information on scientific aspects of the SuperMemo method, see Theoretical aspects of spaced repetition in learning and Optimization of learning.

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