• DocumentCode
    2467310
  • Title

    Research of Student Model Based on Bayesian Network

  • Author

    Yang, Qing ; Wang, Xiuping ; Huang, Zhufeng ; Zheng, Shijue

  • Author_Institution
    Central China Normal Univ., Wuhan
  • fYear
    2007
  • fDate
    23-25 Nov. 2007
  • Firstpage
    514
  • Lastpage
    519
  • Abstract
    With the development of network technology, distance-education research is increasingly valued. Background knowledge and learning objectives of various groups of students on the network are very different. Adaptive education system, which uses different teaching programs for different students, can enhance the efficiency of learning process. In an adaptive education system, the algorithm dealing with uncertainty factors of student model is very important. Bayesian network artifice is a very effective one within various methods dealing with uncertainty. In this paper, we applied Bayesian network method to student model; designed Bayesian network structure in a student model; assigned the local probability distribution and discussed the way to acquire and propagate related evidences. The practice has proven Bayesian network approach for student model is a very effective method.
  • Keywords
    belief networks; computer aided instruction; statistical distributions; teaching; uncertainty handling; user modelling; Bayesian network; adaptive education system; distance education; local probability distribution; student model; teaching; uncertainty handling; Adaptive systems; Bayesian methods; Computer networks; Computer science education; Educational programs; Power system modeling; Probability distribution; Random variables; Space technology; Uncertainty; Adaptive Teaching; Bayesian Network; Student Model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technologies and Applications in Education, 2007. ISITAE '07. First IEEE International Symposium on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-1386-7
  • Electronic_ISBN
    978-1-4244-1386-7
  • Type

    conf

  • DOI
    10.1109/ISITAE.2007.4409338
  • Filename
    4409338