Proceedings of the Annual Meeting of the Cognitive Science Society

Providing coherent explanations of domain knowledge is essential for a fully functioning Intelligent Tutoring System (ITS). Current ITSs that generate explanations directly from domain knowledge offer limited applicability because they place restrictions on the form and extent of the domain knowledge. Moreover,generating explanations in tutors that are designed to teach the breadth of foundational knowledge conveyed in most introductory college courses poses special problems. These problems arise because this knowledge is complex and contains multiple, highly-integrated viewpoints. To overcome these problems, we propose a method for selecting only the knowledge that is relevant for generating a coherent explanation from a desired viewpoint. This method uses domain-independent knowledge in the form of view types to select the appropriate knowledge.