A multi-criteria programming model for intelligent tutoring planning

Authors:
Ruihong Shi;Peng Lu
Affiliations:
Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences;College of Computer Science and Technology, Beijing Institute of Technology
Venue:
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Year:
2006

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Abstract

This paper proposed a practical approach to personalized tutoring planning by exploiting existing tutoring resources (e.g., a book, a courseware). More exactly, it does not build an instructional course from scratch – from the domain curriculum, as most Intelligent Tutoring Systems (ITS) do. Instead, information in the curriculum model is used as metadata, together with other metadata, to describe tutoring resources. Given a learning requirement (learning objectives and/or constraints), it finds out the most appropriate tutoring resource(s) and proposes a proper learning sequence of them. Based on the proposed fuzzy instructional model and learner model, the tutoring planning problem is defined as a multi-criteria programming (MCP) model.