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There is little doubt that examples play a major role in acquiring a new skill. How examples improve learning, however, is subject to some debate. Recently, two different classes of theories have been proposed to explain why examples are such an effective manner of learning. Example Generalization models suggest that problem solving rules are acquired while studying examples.

Knowledge Compilation models, on the other hand, suggest that examples are useful because they guide future problem solving, where the necessary rules are created. Consistent with knowledge compilation models, we found that separating target problems from source examples hindered learning because the source examples could not be remembered to guide problem solving. We also found that if sources are not accessible to remembered during problem solving, learning occurs best when the sources are problems to be solved, rather than examples.

Taken together, these results provide strong support for the knowledge compilation view: in order for an example to be most effective, the knowledge gained from the example must be applied to solve a new problem.