This study appraised the utility of SAT scores in combination with grades in high school courses and the number and quality of these courses in predicting college grades in various fields of study, with the object of providing students with predictions of their academic performance for guidance purposes. The possible impact of this feedback on the flow of students into these fields was also assessed. Data for an entering class at a large state university were used. The SAT and collateral variables were able to predict college grades in different academic areas by taking account of marked variations in grade distributions among fields. These predictions could be potentially useful in guidance. Students' predicted grades in the fields and their intended majors were unrelated, and many students had their highest predicted grades in the humanities, though few intended to major in this field. Hence this feedback would probably stimulate students to take courses or major in the humanities.
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References
1.
American College Testing Program. (1993). The high schoolprofile report, nornative data. Iowa City, IA: Author.
2.
Bennett, G. K. , Seashore, H. G., & Wesman, A. G. (1984). Technical supplement, Differential Aptitude Tests, forms Vand W. Cleveland, OH: Psychological Corporation.
3.
Berryman, S. E. (1983). Who will do science?New York: Rockefeller Foundation.
4.
Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37-46.
5.
Cohen, J. (1968). Nominal scale agreement with provision for scaled disagreement or partial credit. Psychological Bulletin, 70, 213-220.
6.
Cohen, J. , & Cohen, P. (1983). Applied multiple correlation/regression analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
7.
College Board. (1993). College-bound seniors-1993 profile of SAT and Achievement Test takers. New York: Author.
8.
Dempster, A. P. , Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, 39, 1-22.
9.
Dey, E. L. , Astin, A. W., & Kom, W. S. (1991). The Americanfreshman: Twenty-five year trends. Los Angeles: University of California at Los Angeles, Higher Education Research Institute.
10.
Donlon, T. F. (Ed.). (1984). The College Board technical handbook for the Scholastic Aptitude Test and Achievement Tests. New York: College Entrance Examinations Board.
11.
Eells, K. (1961). How effective is differential prediction in three types of college curricula? Educational and Psychological Measurement, 21, 459-471.
12.
Frane, J. (1990). Description and estimation of missing data. In W. J. Dixon (Ed.), BMDP statistical software manual (pp. 813-829). Los Angeles: BMDP.
13.
French, J. W. (1963). Comparative prediction of college major-field grades by pure-factor aptitude, interest, and personality measures. Educational and Psychological Measurement, 23, 767-774.
14.
French, J. W. (1964). Comparative prediction of high-school grades by pure-factor aptitude, information, and personality measures. Educational and Psychological Measurement, 24, 321-329.
15.
Goldman, R. D. , & Hewitt, B. N. (1975). Adaptation-level as an explanation for differential standards in college grading. Journal of Educational Measurement, 12, 149-161.
16.
Hackett, G. (1985). Role of mathematics self-efficacy in the choice of math-related majors of college women and men: A path analysis. Journal of Educational Psychology, 32, 47-56.
17.
Katz, M. , & Nonfis, L. (1972). The contribution of academic interest measures to the differential prediction of marks. Journal of Educational Measurement, 9, 1-11.
18.
Little, R. J. A. , & Rubin, D. B. (1987). Statistical analysis with missing data. New York: John Wiley.
19.
Mollenkopf, W. G. (1950). Predicted differences and differences between predictions. Psychometrika, 15, 409-417.
20.
National Science Foundation. (1990). Women and minorities in science and engineering (NSF 90-301). Washington, DC: Author.
21.
Noeth, R. J. (1979). Counselor's guide and technical summary, 1979-80, Washington Pre-College Test. Seattle, WA: Washington Pre-College Testing Program.
22.
Peterson, K. L. , & Roscoe, B. (1983). Factors influencing selections of major by college females. College Student Journal, 17, 29-34.
23.
Prather, J. E. , Smith, G., & Kodras, J. E. (1979). A longitudinal study of grades in 144 undergraduate courses. Research in Higher Education, 10, 11-24.
Ramist, L. , Lewis, C., & McCamley, L. (1990). Implications of using freshman GPA for the predictive validity of the SAT. In W. W. Willingham, C. Lewis, R. Morgan, & L. Ramist (Eds.), Predicting college grades: An analysis of institutional trends over two decades (pp. 253-288). Princeton, NJ: Educational Testing Service.
26.
Rever, P. R. (1973). Scientific and technical careers: Factors influencing development during the educational years (Monograph 12). Iowa City, IA: American College Testing Program.
27.
Rohr, M. E. , & Ayers, J. B. (1973). Relationship of student grade expectations, selected characteristics, and academic performance. Journal of Experimental Education, 41(3), 58-62.
28.
Simpson, E. H. (1951). The interpretation of interaction in contingency tables. Journal of the Royal Statistical Society, 13, 238-241.
29.
Stricker, L. J. , Rock, D. A., & Burton, N. W. (1991). Sex differences in SATpredictions of college grades (College Board Report 91-2; ETS Research Report 91-38). New York: College Entrance Examination Board.
30.
Stricker, L. J. , Rock, D. A., & Burton, N. W. (1993). Sex differences in predictions of college grades from Scholastic Aptitude Test scores. Journal of Educational Psychology, 85, 710-718.
31.
Stricker, L. J. , Rock, D. A., Burton, N. W., Muraki, E., & Jirele, T. J. (1994). Adjusting college grade point average criteria for variations in grading standards: A comparison of methods. Journal of Applied Psychology, 79, 178-183.
32.
Willingham, W. W. , & Breland, H. M. (1982). Personal qualities and college admissions. New York: College Entrance Examination Board.
