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A Multi-Criteria Programming Model for Intelligent Tutoring Planning

  • Ruihong Shi
  • Peng Lu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4251)

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.

Keywords

Learning Object User Model Learning Plan Learning Topic Mastery Level 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ruihong Shi
    • 1
    • 2
  • Peng Lu
    • 3
  1. 1.Key Laboratory of Intelligent Information ProcessingInstitute of Computing Technology, Chinese Academy of Sciences 
  2. 2.Graduate School of the Chinese Academy of Sciences 
  3. 3.College of Computer Science and TechnologyBeijing Institute of Technology 

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