Multi Agent Learning Styles Based Intelligent Tutoring System

This paper explores a new approach of using the four learning styles to modeling the student in an intelligent tutoring system (ITS), by providing a student model which learns new solutions from the student by considering the four learning styles as the several paths to the student knowledge. This solution will be possible through the multiple-agent software built into this new system that will enable modeling of several possible solution paths when monitoring the student learning process and keeping track of the best path (learning styles) to the student-s solution. This capability is an improvement compared to the previous research reported in literature, using the different learning styles as a path to the student knowledge. The student model is extended by providing a learning module, which is capable of recognizing new solution provided by the student. These new solutions will now be included in the expert system knowledge base. Therefore in this paper, the concepts and implementation of the current ITS as well as the different modeling methods used will be explored. We exhaustively discussed the several learning styles, such as Auditory Learners (through hearing), Visual Learners (through seeing), Kinesthetic Learners (through touch or practice) and hybrid (combination of two or more) will be used as paths to students solution or path to students knowledge while modeling the student.