A case-based reasoning approach to intelligent tutoring system by considering learner style model
Mahmood Kharrat, Nima Reyhani, Kambiz Badie · 2003
We propose an intelligent tutoring system, which uses the parameters of learner model for personalizing the essential courseware in a certain field. Pattern analysis amp; understanding has been selected as a platform for both implementing our approach, since it can be applied equally to a wide range of engineering branches, and can, at the same time, be used as a systemic discipline for nonengineering areas as well. The learner style model that has been used in our system is based on Dunn and Dunn, Kolb, and Myers-Briggs theories. Having the learner models of different users, together with the suitable arrangements of the essential courseware, we will show how a case-based reasoning approach based on a process of case adaptation can yield producing a novel courseware arrangement.