DEVELOPING ADAPTIVE E-EDUCATION SYSTEM BASED ON LEARNING STYLES

Abstract

In this paper, we present an approach to e-learning personalization based on data mining. Currently, many researches show that high number of e-learning courses resulted in failure due to “universal size” concept as the same static content is presented to all students and objective is getting the learner online and ‘into’ the technology. Developing effective e-learning framework depends on finding sophisticated means for discovering students’ goals, preknowledge, needs and motivation. Primary goal of the research is to perform personalizing of distance education system, according to students’ learning styles, goals, background, presentation preferences and performance requirements. Learning Management Systems (LMS) generate lot of data and much information can be discovered using data mining techniques. In order to improve process of using data mining tools and techniques in e-learning systems, we have identified its main phases and requirements. In addition, research that dealt with appliance of clustering technique in a real e-learning system was carried out. Data were collected from the courses within distance education system in Laboratory for E-Business on the Faculty of Organizational Sciences in Belgrade.