• DocumentCode
    3274521
  • Title

    Grey relational analysis of students´ behavior in LMS

  • Author

    Wu, Ai-Lun ; Wu, Shun-Jyh ; Lin, Shu-Ling

  • Author_Institution
    Dept. of Digital Literature & Arts, St. John´´s Univ., Taipei, Taiwan
  • Volume
    2
  • fYear
    2011
  • fDate
    10-13 July 2011
  • Firstpage
    597
  • Lastpage
    602
  • Abstract
    The purpose of this study is to understand how student behave in the online learning environment Moodle. By using Grey relational analysis to understand and to predict students´ grades, researchers are interested in understanding if there is any association between students´ interactivities and their final grades in Moodle system. We developed online materials for two-semester elementary calculus for the first-year students in college of management of a general University in Taiwan. The current data are collected from the online activities of the first semester, whose topics cover the introductory review through derivatives of exponential and logarithmic functions. Twelve online quizzes are built up to include all important topics of the coverage. GRA results are obtained from this group, so we can understand which online quiz activity is significantly correlated with students´ final grades.
  • Keywords
    computer aided instruction; educational administrative data processing; grey systems; GRA; LMS; Moodle; grey relational analysis; logarithmic functions; online learning environment; online materials; online quizzes; students behavior; students grade prediction; two semester elementary calculus; Correlation; Cybernetics; Educational institutions; Machine learning; Measurement; Proposals; Course management system (CMS); Grey relational analysis (GRA); Learning management system (LMS); Moodle; Online course design; Online learning; Students´ online behavior;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
  • Conference_Location
    Guilin
  • ISSN
    2160-133X
  • Print_ISBN
    978-1-4577-0305-8
  • Type

    conf

  • DOI
    10.1109/ICMLC.2011.6016794
  • Filename
    6016794