• DocumentCode
    2914515
  • Title

    A Remodeling Method of Automatic Learning Process Based on LMS in E-Learning

  • Author

    Li, Yan

  • Author_Institution
    Sch. of Econ. & Manage., Shanghai Maritime Univ., Shanghai, China
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    565
  • Lastpage
    569
  • Abstract
    In e-learning, online-learning management system (LMS) as an open electronic platform supports learning and teaching from different places. LMS can realize collaboration of learning process. Exact learning process can ensure the normal running of LMS. With the constantly change of teaching environment, learning process models don´t keep stable. The large mount of process logs are saved in LMS. These logs involve information of various learning processes. This paper researches an automatic learning process mining and remodeling method based on logs. The core of the method is process mining rules and remodeling algorithm. In this method a Markov transition matrix is set up based on process logs. And according to the matrix the eight mining rules of process logical relations are designed. The remodeling algorithm can not only automatically remodel the various learning processes, but also greatly enhance the process modeling efficiency.
  • Keywords
    data mining; educational administrative data processing; Markov transition matrix; automatic learning process; logical relations process; online learning management system; process logs; process mining; process remodeling algorithm; Algorithm design and analysis; Collaboration; Collaborative work; Computer aided instruction; Computer networks; Conference management; Content management; Education; Electronic learning; Least squares approximation; E-learning; Markov transition matrix; Online-learning management system; Process log; Process mining; Process remodeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Information Systems and Mining, 2009. WISM 2009. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3817-4
  • Type

    conf

  • DOI
    10.1109/WISM.2009.120
  • Filename
    5369262