DATA MINING AS A TECHNIQUE TO ANALYZE THE LEARNING STYLES OF STUDENTS IN USING THE LEARNING MANAGEMENT SYSTEM

Higher education is becoming a big business, with huge investments in IT technology supporting Learning Management System (LMS). LMS is a software application which is used by student in learning process. The purpose of this paper is to analyze the use of LMS based on activities and results of student learning and seeks to address the interface between individual learning that use LMS data to support decision-making and course design. A model of data warehouse is built to evaluate by means of a case study the usefulness validity of analyses performed. Data mining is considered the non-trivial extraction of implicit, previously unknown, and potentially useful information from data. This paper analyzes students’ activities records using LMS then building a data warehouse, and data mining. The paper finds that after mining data, students can be classified into different groups according to the activities using LMS. The data mining results shows that students can be categorized into four clusters; each cluster has its own characteristics. Integration of data warehouse, data mining and LMS produce a framework that uses transactional data to be transformed into knowledge that can be used to maximize the teaching-learning process of lecturer and students.