Facilitating deep learning through self-explanation in an open-ended domain

Self-explanation has been used successfully in teaching Mathematics and Physics to facilitate deep learning. We are interested in investigating whether self-explanation can be used in an open-ended, ill-structured domain. For this purpose, we enhanced KERMIT, an intelligent tutoring system that teaches conceptual database design. The resulting system, KERMIT-SE, supports self-explanation by engaging students in tutorial dialogues when their solutions are erroneous. The results of an evaluation study indicate that self-explanation leads to improved performance in both conceptual and procedural knowledge.

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