Development of Knowledge Based Intelligent Tutoring System

Intelligent Tutoring Systems (ITS) are computer-based tutors which act as a supplement to human teachers. The major advantage of an ITS is it can provide personalized instructions to students according to their cognitive abilities. The classical model of ITS architecture has three main modules – domain, model, student model and teaching model. In this chapter, we have discussed the recent developments in those areas and tried to address the important issues involved with them. We have developed an ITS. We have used two major data structures (a tree and a directed graph) to represent the domain knowledge within the domain model. The domain model also consists of a repository which is a collection of study and test materials. The contents in the repository are annotated using various informative tags for intelligent retrieval of them for the students. A fuzzy state based student model is used to represent a student’s cognitive ability and learning behavior. This is an important task as the adaptation techniques to be followed by the system are dependent to the student’s ability. The actual adaptation techniques are planned and executed by the control engine, which is the teaching model of the system. The control engine communicates with the domain and the student model and takes decisions using fuzzy rules. We have evaluated our ITS and found quite encouraging results.