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E-learning Behavior Analysis Based on Fuzzy Clustering

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4 Author(s)
Jili Chen ; Coll. of Educ. Sci. & Technol., Huanggang Normal Univ., Huanggang, China ; Kebin Huang ; Feng Wang ; Huixia Wang

E-learning behavior analysis is an important issue to the instruction based on Internet. This paper proposed a new method to analyze the e-learning behavior. It classified e-learning behaviors into several clusters by fuzzy clustering algorithm. Behaviors in the same cluster have the most common in characters, while behaviors between clusters have the least common. Experiments fully demonstrated that the proposed method can achieve good performance of analyzing e-learning behavior. It shows that by using cluster analysis, teachers can understand the students better in interest, personality and other informations. It also helps to develop effective educational resource and carry out the personalized instruction.

Published in:

Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on

Date of Conference:

14-17 Oct. 2009

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