An Adaptive Personalized E-learning Model Based on Agent Technology

摘要

Due to overall popularity of the Internet, E-learning has become a lot methods of learning in recent years. Through the Internet, learners can freely absorb new knowledge without the restriction of time and place. Based on individual difference of learner's abilities and preferred learning styles in hypermedia environment, the learning outcomes vary essentially. Meanwhile, with the development of E-learning technologies, learners can be provided more effective learning environment to optimize their learning. Adaptive E-learning systems are built to personalize and adapt E-learning content, pedagogical models, and interactions between participants in the environment to meet the individual needs and preferences of users if and when they arise. In our paper, we first 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.