![]() ![]() Ahmad, "Multi-Agent Based E-Learning Systems: A Comparative Study," in Proceedings of the 2014 International Conference on Information and Communication Technology for Competitive Strategies, New York, NY, USA, Oct. Felder, "Learning and Teaching Styles in Engineering Education," Journal of Engineering Education -Washington-, vol. Sadik, "The Impact of Learning Styles on Learner's Performance in E-Learning Environment," International Journal of Advanced Computer Science and Applications, vol. Qtaish, "Effective Adaptive E-Learning Systems According to Learning Style and Knowledge Level," Journal of Information Technology Education: Research, vol. Larbi, "Outlining an Intelligent Tutoring System for a University Cooperation Information System," Engineering, Technology & Applied Science Research, vol. The system will be able to provide the students with a sequence of learning objects that matches their profiles for a personalized learning experience.Īdaptative e-learning system, knowledge level, learning path recommendation, learning styles, multi-agent, Q-learning, reinforcement learning, students’ disabilities Three types of disabilities were taken into account, namely hearing impairments, visual impairments, and dyslexia. ![]() The proposed system is focused on three principal characteristics, the learning style according to the Felder-Silverman learning style model, the knowledge level, and the student's possible disabilities. The main objective of this system is the recommendation to the students of a learning path that meets their characteristics and preferences using the Q-learning algorithm. In this paper, a design of an adaptative e-learning system based on a multi-agent approach and reinforcement learning is presented. The agents in these systems collaborate to provide a personalized learning experience. The application of the multi-agent approach in adaptive e-learning systems can enhance the learning process quality by customizing the contents to students’ needs. These agents are always in communication and they can be homogeneous or heterogeneous and may or may not have common objectives. ![]() A multi-agent system is a collection of organized and independent agents that communicate with each other to resolve a problem or complete a well-defined objective. These systems are able to suggest the student the most suitable pedagogical strategy and to extract the information and characteristics of the learners. Received: 26 October 2020 | Revised: 3 November 2020 | Accepted: 5 November 2020 | Online: 6 February 2021Īdaptive e-learning systems are created to facilitate the learning process. ![]()
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