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Intelligent Tutorial Planning Based on Extended Knowledge Structure Graph

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3942))

Abstract

Intelligent tutorial planning (ITP) is an important component of intelligent tutorial system (ITS). Models of domain knowledge, models of tutorial methods and models of learner are three key elements of ITS. In this paper, the concept of extended knowledge structure graph (EKSG) is presented. An EKSG integrates models of domain knowledge, models of tutorial methods and models of learner organically. Based on the EKSG, algorithms JUDGE and TPLAN are put forward to resolve ITP problems. The algorithm JUDGE calculates the optimal solution graph when there is a solution, and the algorithm TPLAN calculates optimal tutorial plan based on the solution graph. Both algorithms are proved to be correct, the efficiency of them is also discussed.

This work is partially supported by the National Natural Science Foundation of China Grant #60234030 and Master Excellent Course Project of China and CSU.

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© 2006 Springer-Verlag Berlin Heidelberg

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Duan, Z., Jiang, Y., Cai, Z. (2006). Intelligent Tutorial Planning Based on Extended Knowledge Structure Graph. In: Pan, Z., Aylett, R., Diener, H., Jin, X., Göbel, S., Li, L. (eds) Technologies for E-Learning and Digital Entertainment. Edutainment 2006. Lecture Notes in Computer Science, vol 3942. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11736639_5

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  • DOI: https://doi.org/10.1007/11736639_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33423-1

  • Online ISBN: 978-3-540-33424-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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