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Intelligent Tutorial Planning Based on Extended Knowledge Structure Graph

  • Zhuohua Duan
  • Yunfei Jiang
  • Zixing Cai
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Domain Knowledge Optimal Planning Main Loop Intelligent Tutoring System Edge Node 
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

  • Zhuohua Duan
    • 1
    • 3
  • Yunfei Jiang
    • 2
  • Zixing Cai
    • 3
  1. 1.Department of Computer, School of Information EngineeringShaoguan UniversityShaoguanChina
  2. 2.Institution of SoftwareSUN YAT-SEN UniversityGuangzhouChina
  3. 3.College of Information Science and EngineeringCentral South UniversityChangshaChina

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