VanLehn, K., Ball, W. & Kowalski, B. (1990). Explanation-based learning of correctness: Towards a model of the self-explanation effect. In M. Piatelli-Palmarini (Ed.) Proceedings of the Twelfth Annual Conference of the Cognitive Science Society, 717-724. Earlbaum: Hillsdale, NJ.

Two major techn.iques in machine learning, explanation-baSed learning and explanation completion, are both superficially plauslble. models for Chi s self-explanatlon effect, wherein the amount of explanation given to examples while studying them correlates with the amount the subject learns from them. We attempted to simulate Chi's protocol data With the simpler of the two learning processes, explanation completion, in order to find out how much of the self-explanation effect it could account for. Although explanation completion did not turn out to be a good model of the data, we discovered a new learning technique, called explanation-based learnmg of correctness, that combines explanation-based learning and explanation completion and does a much better job of explaining the protocol data The new learning process is based on the assumption that subjects use a certain kind of plausible reasoning.

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