Multi-Agent Adaptive E-Learning System Based On Learning Styles
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Date
2021
Authors
Kivuva, Faith Ngami
Maina, Elizaphan
Journal Title
Journal ISSN
Volume Title
Publisher
Center for Open Access in Science
Abstract
Most traditional e-learning system fails to provide the intelligence that a learner may require
during their learning process. Different learners have different learning styles but the current elearning systems are not able to provide personalized learning. In this paper, we discuss how
intelligent agents can aid learners in their learning process. Three agents have been developed
namely, learner agent, information agent, and tutor agents that will be integrated into a learning
management system (Moodle). Learners are provided with a personalized recommendation
based on the learning styles.
Description
Article
Keywords
personalized feedback, Moodle, intelligent agents, learning styles, recommedation
Citation
Kivuva, F. N., Maina, E., & Gitonga, R. (2021). Multi-Agent Adaptive e-Learning System Based on Learning Styles. Open Journal for Information Technology, 4(1), 1.