Publication

Abstract : The learning style of individual students differs from each other. Hence the common way of teaching a course for all the students with same course material, in the existing education system, becoming unsuccessful for the present generation of student community. As a solution to this problem constructing different courseware based on the learning style of the students is an open and challenging research problem. This paper proposes an approach for personalized courseware construction by integrating the Evolutionary Computing (EC) approach with a Data Mining (DM) technique. This proposed approach uses Differential Evolution (DE) algorithm for generating association rules for student learning style models so that relevant materials can be provided for the courseware based on the students‟ requirements and interest. The sample data from FelderSilverman learning style is used for forming rules using DE to extract useful information for courseware recommendation. This paper presents this proposed approach in detail.