• DocumentCode
    2251387
  • Title

    A new method to evaluate students´ learning achievement by automatically generating the importance degrees of attributes of questions

  • Author

    Chen, Shyi-Ming ; Li, Ting-Kuei

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
  • Volume
    5
  • fYear
    2010
  • fDate
    11-14 July 2010
  • Firstpage
    2495
  • Lastpage
    2499
  • Abstract
    This paper presents a new method for students´ learning achievement evaluation by automatically generating the importance degrees of the attributes of questions. It considers the “accuracy rate”, the “time rate”, the “importance” and the “complexity” for evaluating students´ learning achievement. First, it transforms the attributes “accuracy rate” and “time rate” into the “effect of accuracy rate” and the “effect of time rate”, respectively. Then, it generates the weights of the attributes “effect of accuracy rate”, “effect of time rate”, “importance” and “complexity”, respectively. Then, it generates the importance degrees of the attributes of questions based on the weights of the attributes. Then, it calculates the learning achievement indices of the students having the same total score. Finally, it determines the new ranking order of the students having the same original total score based on the learning achievement indices of the students. The proposed method is simpler than Bai and Chen´s method due to the fact that it is based on simple arithmetic calculations rather than the complicated fuzzy reasoning method.
  • Keywords
    education; fuzzy set theory; Bai method; Chen method; accuracy rate; attribute weight; fuzzy reasoning method; question attributes; student learning achievement indices; students learning achievement evaluation; time rate; Accuracy; Complexity theory; Cybernetics; Fuzzy reasoning; Fuzzy sets; Machine learning; Tin; Fuzzy sets; Learning achievement index; Membership functions; Students´ learning achievement evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-6526-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2010.5580818
  • Filename
    5580818