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

Issue title: Innovational Soft Computing

Article type: Research Article

Authors: Weerasinghe, Amali^{; *} | Mitrovic, Antonija

Affiliations: Intelligent Computer Tutoring Group, Department of Computer Science, University of Canterbury, Private Bag 4800, Christchurch, New Zealand

Correspondence: [*] Corresponding author. E-mail: acw51@student.canterbury.ac.nz

Abstract: 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.

DOI: 10.3233/KES-2006-10101

Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 10, no. 1, pp. 3-19, 2006