Intelligent tutorial planning based on extended knowledge structure graph

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. © Springer-Verlag Berlin Heidelberg 2006.