Fostering Adaptivity in E-Learning Platforms: A Meta-Model Supporting Adaptive Courses

نویسنده

  • Sabine Graf
چکیده

E-Learning platforms are very successful in e-education but provide little adaptivity. Personalized courses which adapt to the needs of each individual learner improve the learning progress. In this paper, we introduce a meta-model for enhancing e-learning platforms with the use of adaptivity. This meta-model enables the platforms to provide different courses that adjust to the needs of each learner, especially with respect to learning styles. The paper presents the metamodel by describing the structure of an adaptive course and exemplifies different views for learners with different learning styles.

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تاریخ انتشار 2005