Self-Explanations: How Students Study and Use Examples in Learning to Solve Problems

摘要

The present paper analyzes in detail (talk-aloud protocols) 'Good' and 'Poor' students' initial encoding of worked-out examples of mechanics problems, and their subsequent reliance on examples during problem solving. We find that 'Good' students learn with understanding: they generate many explanations which refine and expand the conditions for the action parts of the example solutions, and relate these actions to principles in the text. These self-explanations are guided by accurate monitoring of their comprehension failures and successes. Such learning results in an example-independent knowledge and in a better understanding of the principles presented in the text. 'Poor' students do not generate sufficient self-explanations, inaccurately monitor their learning and subsequently rely heavily on examples. The results are discussed relating these psychological findings to existing AI models of explanation-based generalizations.