Expert Systems as a tool for Knowledge Representation in teaching & learning Process

Abstract

In the last years, Intelligent Tutoring Systems have been a very successful way for improving teaching & learning experience. Many issues must be addressed until this technology can be defined mature. One of the main problems within the Intelligent Tutoring Systems is the process of contents authoring: knowledge acquisition and manipulation processes are difficult tasks because they require a specialized skills on computer programming and knowledge engineering.
In this research we discuss a general framework for knowledge management in an Intelligent Tutoring System and propose a mechanism based on first order data mining to partially automate the process of knowledge acquisition that have to be used in the ITS during the tutoring process. Such a mechanism can be applied in Constraint Based Tutor and in the Pseudo-Cognitive Tutor.
We design and implement a part of the proposed architecture, mainly the module of knowledge acquisition from examples based on first order data mining. We then show that the some topics of intelligence tutoring system. Finally, we discuss the limitation of current approach and the possible improvements of the whole framework for Expert tutoring Programs in teaching & learning process.