DocumentCode
3346165
Title
E-learning Behavior Analysis Based on Fuzzy Clustering
Author
Jili Chen ; Huang, Kebin ; Feng Wang ; Wang, Huixia
Author_Institution
Coll. of Educ. Sci. & Technol., Huanggang Normal Univ., Huanggang, China
fYear
2009
fDate
14-17 Oct. 2009
Firstpage
863
Lastpage
866
Abstract
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.
Keywords
computer aided instruction; fuzzy logic; pattern clustering; Internet; e-learning behavior analysis; educational resource; fuzzy clustering; personalized instruction; Algorithm design and analysis; Clustering algorithms; Clustering methods; Educational institutions; Educational technology; Electronic learning; Genetics; Internet; Pattern recognition; Statistical analysis; E-learning behavior; fuzzy cluster; pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on
Conference_Location
Guilin
Print_ISBN
978-0-7695-3899-0
Type
conf
DOI
10.1109/WGEC.2009.214
Filename
5402847
Link To Document