Research on Grouping Strategy of Virtual Learning Community Based on the Fuzzy C-means Clustering

Abstract

Abstract-Virtual learning community, as a new model of network education, is widely used in the process of learning. But this kind of way is not gradually satisfying people's needs for more intelligent and personalized. Teaching strategy in virtual learning community is an important research direction of intelligent reasoning and it is the key to realize intelligent which has great role in promoting for it. In this paper, the fuzzy cmeans clustering algorithm is applied to analysis of the characteristics of learning and grouped from the perspective of teaching strategy and reasoning in virtual learning community. And the model of teaching strategy reasoning mechanism based on learning characteristics is designed which use the cosine similarity and grouping clustering center vector and teaching part of the matching degree of policy rule conditions by setting the threshold of matching processing. Formulate specific feasible learning tasks and teaching strategies will be made for the learners. Through the simulation experiments it is found that the teaching strategy reasoning algorithm is feasible and it has achieved good results.Keywords-virtual learning community; the fuzzy c-means clustering algorithm; learning characteristic; teaching strategy reasoning mechanism.