Design of an adaptive curriculum portfolio recommendation system by learning object similarity evaluation and group decision modeling

Thanks to the drastic proliferation of Internet, e-learning has been recognized as an effective media for various kinds of learners. However, the tremendous course materials in the Internet may make learners be confused in choosing their suitable course materials. In this paper, we propose an approach to construct an adaptive curriculum portfolio recommendation system. It offers tailored course materials for learners based on the following processes: 1. Courses Similarity Analysis: By calculating similarity to find the relationship among courses. 2. Group Decision Making: By integrating teachers' experience to produce curriculum portfolios. To offer users an adaptive environment, we take into account the following processes: 1. Preference of learner: Students can setup their own preference relations of criteria for generating customized curriculum portfolios. 2. Adopting the Degrees of Understanding of users: By allowing users to setup the degrees of understanding based on their own knowledge background. Based on our approach, learners can be benefited from the group decision-making process, and obtain customized course materials based on their own criteria.