Improving Interactivity in e-Learning Systems with Multi-agent Architecture
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ICWL'05 Proceedings of the 4th international conference on Advances in Web-Based Learning
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IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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Computers & Education
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Adaptive e-learning system, deal with appropriate personalization and adaptation techniques in order to maximize the effectiveness of learning. Customer preference and personality are going to be more and more important to e-learning. This paper first hopes to explain the grid agent e-learning model, whose main actions including registry, directory and discovery. Through these actions, the manager's agent will find out the suitable learning services. Secondly, to implement the adaptability of the Grid agent model, the method of Artificial Psychology and how to realize adaptive personalized e-learning by this method so that are the student's agent can employ the learning material matched to their own personality type are also emphasized. The experiment data also supported our assumption that the learners may perform better if they use our adaptive grid agent model.