An agent-based personalized distance learning system for delivering appropriate studying materials to learners

Abstract

In this paper, we propose an agent-based personalized distance learning system for delivering appropriate studying materials to learners by judging learners degree of understanding. The main elements of our proposed system are the agents, which play the role of teacher and based on the learning history they analyze the understanding degree of learners. To evaluate the proposed distance learning system, we carried out three experiments and a questionnaire investigation. The evaluation results show that by making grouping of learners the agents can decide what kind of materials should be given to learners. We show that by adding new features such as mental action of color and the competition with other learners, the learners will increase furthermore the learning efficiency.