• 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