• DocumentCode
    584860
  • Title

    SAPM: ANFIS based prediction of student academic performance metric

  • Author

    Zuviria, N.M. ; Mary, S.L. ; Kuppammal, V.

  • Author_Institution
    Nat. Coll. of Eng., Tirunelveli, India
  • fYear
    2012
  • fDate
    26-28 July 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    A methodology for evaluating the academic performance metric of students is proposed in this paper based on their performance in periodic assessment tests, attendance and complexity of the question set. These are the major features determining the students learning efficiency evaluation. The impact of these metrics plays a major role in predicting the final grade of a student. The application of adaptive neuro fuzzy inference system helps to model the frame work for evaluating Student Academic Performance Metric(SAPM). The outcome of this methodology can be used to classify the students based on their academic skill and helpful in predicting the probability of their success in the final examinations.
  • Keywords
    computational complexity; computer aided instruction; fuzzy neural nets; fuzzy reasoning; ANFIS based prediction; SAPM; adaptive neuro fuzzy inference system; question set complexity; student academic performance metric; students learning efficiency evaluation; Complexity theory; Measurement; SAPM; adaptive neuro fuzzy inference system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing Communication & Networking Technologies (ICCCNT), 2012 Third International Conference on
  • Conference_Location
    Coimbatore
  • Type

    conf

  • DOI
    10.1109/ICCCNT.2012.6396065
  • Filename
    6396065