Research And Implementation Of Web-Based Collaborative Learning Student Grouping System Based On Fuzzy Theory

Collaborative learning is an effective learning mode. The research and application on WBCL (Web-based collaborative learning) are prevailing over the field of education technology. Collaborative learning grouping is a basic factor of collaborative learning mode. It is a key for successful collaborative learning to group. Therefore, the research problem is how to group scientifically and reasonably.This dissertation analyzed the correlative factor on influencing collaborative learning based the theories of collaborative learning. The student characteristics should be considered emphatically during grouping, which is learning style, academic achievement and sex. The fuzzy clustering theory was used to analyse learning style. Through designing fuzzy clustering arithmetic, using matlab technique to implement learning style clustering analysis, the students were classified accurately. It ensured maximum homogeneous and heterogeneous grouping.The system considered learning style, academic achievement and sex and followed the principle of homogeneous grouping and heterogeneous grouping. The technique of ASP, Matlab and correlative database were used and student grouping system of B/S system structure was designed and complemented.The system achieved mulit-grouping mode. It can complete the function that the teacher automatically choose different grouping mode according to learning subjects. The students will release their feeling after they have studied in a learning group. The teachers can know if the grouping modes need to be changed based on the subjects.This dissertation makes up the correlative theory of correlative learning and presents the environment of automatic grouping. It will become an effective tool for teaching and scientific research.