A Personalised Learning Environment Architecture for E-Learning

T. Ninomiya, H. Taira, and T. Okamoto (Japan)


e-Learning, monitoring system, learning object metadata (LOM), agent, personalised contents, genetic algorithm (GA) Figure 1. WebClass RAPSODY Content DataBase Learner fs Attribute DataBase Learning Log DataBase Video Camera PDAPC Mobile Encoder Group BBS Knowledge Sharing Authoring Module Learning Module (Self / Group) Personalised Contents Module Analysis Module Mail Streaming VOD Text/ LaTeX/ Image Flash/ JAVA movie etc. Discuss


A system architecture for a personalised learning environment in e-Learning is described. First, we present an overview of our learning management system, WebClass RAPSODY, developed for use by the entire student body in a university. Then, a new function including a unit for learning mode to monitor and analyse learners’ learning status and a unit for contents to search and analyse the content status is explained. In the unit for learning mode, access files are made at each login from which data indicating the learner’s status are generated. In the unit for contents, an agent searches and corrects educational elements of LOM from various LMS, and data indicating the content’s status are generated in the LOM database. After learning a given content, this system indicates the next suitable content, using both data of learner’s status and content status using a genetic algorithm (GA). This function is capable of supporting learners to sustain e-Learning with good understanding of contents and a high degree of motivation to learn.

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