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
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