Intelligent tutorial planning based on extended knowledge structure graph

  • Authors:
  • Zhuohua Duan;Yunfei Jiang;Zixing Cai

  • Affiliations:
  • Department of Computer, School of Information Engineering, Shaoguan University, Shaoguan, Guangdong, China;Institution of Software, SUN YAT-SEN University, Guangzhou, Guangdong, China;College of Information Science and Engineering, Central South University, Changsha, Hunan, China

  • Venue:
  • Edutainment'06 Proceedings of the First international conference on Technologies for E-Learning and Digital Entertainment
  • Year:
  • 2006

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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.