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Curriculum Knowledge Representation and Manipulation in Knowledge-Based Tutoring Systems
October 1996 (vol. 8 no. 5)
pp. 679-689

Abstract—A Knowledge-Based Tutoring System (KBTS) is a computer-based instructional system that uses artificial intelligence techniques to help people learn some subjects. We found that the knowledge communication process involving a KBTS and a human student can be decomposed into a series of communication cycles, where each cycle concentrates on one topic and contains four major phases: planning, discussing, evaluating and remedying. The major contributions of this work are the development of a generic architecture for supporting the knowledge communication between a KBTS and a student, and a graphical notation and schema for supporting the curriculum knowledge representation and manipulation during the planning phase of a tutoring process. The curriculum knowledge about a course can help a tutoring system determine the sequences in which the topics will be discussed with the students effectively and diagnose the students' mistakes. The curriculum knowledge base contains the goal structure of the course, prerequisite relations, and multiple ways of organizing topics, among others. As an example, we have focused on developing SQL-TUTOR, a KBTS for the domain of SQL programming. This system has features such as efficient control mechanism, explicit curriculum knowledge representation, and individualized private tutoring. For allowing the students relative freedom to decide how to study the domain knowledge about a subject, the system provides the students with a group of operators to hand-tailor the learning schedules according to their special backgrounds, requests, and interests.

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Index Terms:
Computer in education, intelligent tutoring, knowledge representation and manipulation, topic association graph, learning graph, curriculum management.
Citation:
Gang Zhou, Jason T.-L. Wang, Peter A. Ng, "Curriculum Knowledge Representation and Manipulation in Knowledge-Based Tutoring Systems," IEEE Transactions on Knowledge and Data Engineering, vol. 8, no. 5, pp. 679-689, Oct. 1996, doi:10.1109/69.542023
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