Adaptive Help System Based on Learners' Digital Traces and Learning Styles in the ILE
Bentaib Mohssine, Mohammed Aitdaoud, Khalil Namir, Mohammed Talbi
Academic Editor: Youssef EL FOUTAYENI
Received |
Accepted |
Published |
01 February 2020 |
16 February 2020 |
10 March 2020 |
Abstract: In the recent years Learning Management System (LMS) such as Claroline, Ganesha, Chamilo, Moodle ..., are commonly and well used in e-education (e-learning). Most of the Interactive Learning Environment (ILE) focus on supporting teachers in the creation and organization of online courses. However, in general, they do not consider individual differences of each learner. In addition, they do not provide enough indicators which will help to track the learners.In this paper, we investigate the benefits of integrating learning styles in the Web-based educational systems. Also, we are interested in the use of interaction traces in order to address the lack of feedback between the learner and the teacher.Generally, we aim to offer a tool that allows the tutor and the instructional designer to interpret learner courses, in order to provide help as needed for each individual using data mining techniques.
