Self-explanations: How students study and use examples in learning to solve problems

Michelene T.H. Chi, Miriam Bassok, Matthew W. Lewis, Peter Reimann, Robert Glaser

Research output: Contribution to journalArticle

1502 Scopus citations

Abstract

The present paper analyzes the self-generated explanations (from talk-aloud protocols) that "Good" and "Poor" students produce while studying 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 own understanding and misunderstanding. Such learning results in example-independent knowledge and in a better understanding of the principles presented in the text. "Poor" students do not generate sufficient self-explanations, monitor their learning inaccurately, and subsequently rely heavily on examples. We then discuss the role of self-explanations in facilitating problem solving, as well as the adequacy of current AI models of explanation-based learning to account for these psychological findings.

Original languageEnglish (US)
Pages (from-to)145-182
Number of pages38
JournalCognitive Science
Volume13
Issue number2
DOIs
StatePublished - Jan 1 1989
Externally publishedYes

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence

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