Adaptive e-learning web-based English tutor using data mining techniques and Jackson's learning styles

Abstract

With the emanation of educational data mining field, it is being increasingly connected to a number of research areas such as adaptive and intelligent web-based tutors, intelligent educational applications and other accommodating online educational data mining systems. The applications of educational data mining takes into account the system academic aspects, the academic background, and the learner's classification. This paper proposes a new adaptive e-learning system. The proposed system integrates a well known intelligent web-based English e-learning tutor with data mining techniques. Also, the data minig techniques are used in order to cluster students' learning styles according to Jackson's learning styles. The ultimate goal of the proposed system is to determine the best teaching pattern for each learner. The proposed system can be made available through the web Everywhere as well as Every Time (EWET). It also offers adaptive facilities such as learning videos, adaptive presentations, and quizzes for the students. Moreover, it helps both teachers and students to follow the best learning process and achieve the highest academic rates. The results show that the highest student's achievement pattern is the pattern (Speaking — Reading — Grammar — Writing) with score of at least 87.4%.