Clustering of Web learners based on rough set
Liu Shuai-dong, Chen Shi-hong · Wuhan University Journal of Natural Sciences · 2004
The demand for individualized teaching from E-learning websites is rapidly increasing due to the huge differences existed among Web learners. A method for clustering Web learners based on rough set is proposed. The basic idea of the method is to reduce the learning attributes prior to clustering, and therefore the clustering of Web learners is carried out in a relative low-dimensional space. Using this method, the E-learning websites can arrange corresponding teaching content for different clusters of learners so that the learners’ individual requirements can be more satisfied.