• DocumentCode
    2427915
  • Title

    Fuzzy Admissions Model

  • Author

    Olivier, Philip D.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Mercer Univ., Macon, GA
  • fYear
    2007
  • fDate
    4-6 March 2007
  • Firstpage
    288
  • Lastpage
    290
  • Abstract
    Some have criticized the SAT based on its inability to predict success of freshman performance, as measured by freshman grade point average. Contrary to this view, this paper shows that the inability of SAT data alone to predict freshman performance as measured by freshman grade point average might be the result of the efficient use of the SAT data to place entering students in the appropriate freshman level mathematics and English courses. This paper also suggests that a nonlinear predictive model based on fuzzy logic techniques might be more accurate than the linear regression model used as the basis of the criticism.
  • Keywords
    education; fuzzy logic; nonlinear systems; regression analysis; English course; fuzzy admissions model; fuzzy logic; linear regression model; mathematics course; nonlinear predictive model; Aggregates; Engineering students; Fuzzy logic; Fuzzy systems; History; Linear regression; Mathematics; Physics; Predictive models; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Theory, 2007. SSST '07. Thirty-Ninth Southeastern Symposium on
  • Conference_Location
    Macon, GA
  • ISSN
    0094-2898
  • Print_ISBN
    1-4244-1126-2
  • Electronic_ISBN
    0094-2898
  • Type

    conf

  • DOI
    10.1109/SSST.2007.352367
  • Filename
    4160853