How do we encourage retention of knowledge in computing?
The scenario described in the experiment below has been repeated many times in the education literature: Students are asked to read some material (or listen to a lecture), and are then asked to do something with that material (e.g., take a quiz, write down everything they can remember, do a mind-mapping exercise), and some time later, they take a test to measure retention. In the experiment described below, simple writing beat out creating a mental map. Interesting, but it’s an instance of a case that I wanted to raise.
This pattern of information+activity+retention is common, and really does work. Doing something with the knowledge improves retention over time.
So how do we do this in computer science? What do we ask our students to do after lecture, or after reading, or after programming, to make it more likely that they retain what they learned? If our only answer is, “Write more programs,” then we missed the point. What if we just had our students write down what they learned? Even if it was facts about the program (e.g., “The test for the sentinel value is at the top of the loop when using a WHILE”), it would help to retain that knowledge later. What this particular instance points out is that the retention activity can be very simple and still be effective. Not doing anything to encourage retention is unlikely to be effective.
But two experiments, carried out by Dr Jeffrey Karpicke at Purdue University, Indiana, concluded that this was less effective than constant informal testing and reciting.Dr Karpicke asked around 100 college students to recall in writing, in no particular order, as much as they could from what they had just read from science material.Although most students expected to learn more from the mapping approach, the retrieval exercise actually worked much better to strengthen both short-term and long-term memory.The results support the idea that retrieval is not merely scouring for and spilling out the knowledge stored in one’s mind — the act of reconstructing knowledge itself is a powerful tool that enhances learning about science.