Effects of self-explanation in an open-ended domain
Self-explanation is used in several intelligent tutoring systems in the domains of Mathematics and Physics to facilitate deep learning. Since these domains are well structured, instructional material to self-explain can be clearly defined. We are interested in investigating whether self-explanation can be used in an open-ended 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. An evaluation study was conducted in July 2002, to investigate whether students will learn better when self-explaining. The results indicate that self-explanation leads to improved performance in both conceptual and procedural knowledge.