A model for an intelligent distance learning system: a preliminary study

Abstract

This paper will focus on the use of artificial intelligence techniques in distance education where the current state of the learner is hypothesized in a knowledge base and instruction is individualized for the learner based on the knowledge learned about the learner. The proposed model consists of several major activities: 1) the development of the student model where different classes of learning styles, capabilities and characters will be identified and transformed into a knowledge base representing different student model; 2) development of the motivational model where different motivational elements that can be used in a distance learning system will be identified and techniques of incorporating the elements into a module to be used by the tutor module will be configured; 3) development of the tutor model where the main inference engine of the system that includes techniques to hypothesize a student and then select a strategy for teaching, assessing, and motivating him throughout the learning process will be built; 4) design of the domain expert model consisting of a set of teaching operations and questions for a chosen subject matter; and 5) development of an intelligent distance learning system prototype based on the models designed.