International Journal of
Information and Education Technology

Abstract

With the rapid development of social economy and the Internet, the network education is becoming a way of teaching which has a wide application range and covering larger area. Virtual learning community (VLC) is a combination of computer technology, psychology, pedagogy and other multi-disciplinary research field and actually a new model of network education. However, the teaching data of VLC are often disorderly, fragmentary, mixed and its value is also not easy to detect. The using of data mining technology will solve this kind of problems and bring many unexpected benefits support the teaching of the VLC. This paper reports on the analysis of learning behavior of the VLC and how to extract the feature vector of learning. The fuzzy c-means clustering algorithm is applied to analyze the learning behavior and divide the students of the VLC by the feature of them. Then some targeted teaching guidance can be made for each group. This kind of grouping strategy is to be found feasible and achieved good effect by simulation experiment.