Projecting acceptance into Millersville University's Department of Industry and Technology using high school rank, social capital, SAT scores, sex, age, and race

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Virginia Tech

The National Council for Accrediting of Teacher Education (NCATE) revised its standards in 1986. Included in this revision was a new entrance criterion for teacher education units: a 2.5 grade point average (GPA). Research indicated that GPA was not a good measure of aptitude or achievement when it was used to compare students. The large error variance involved in using GPA as a measure of aptitude could eliminate many capable teacher candidates. The researcher determined to create a system which would identify students who would not be likely to achieve the 2.5 GPA and which would also suggest methods for motivated students to increase their chances of achieving the 2.5 GPA. A sample was identified: industry and technology students at Millersville University who were sophomores from the fall of 1981 to the fall of 1986. This sample was randomly divided into two groups for the purpose of cross-validation. Multiple regression was used for both the overall group and the two subgroups to create equations which predicted sophomore GPA, using the following independent variables: SAT scores, high school rank, age, sex, race and human social capital.

Students who were over 23 years old when they entered the program were eliminated from the study because SAT scores or high school ranks were not available for most of them. Predictors with a significance level of 0.05 had the following squared correlations to sophomore GPA: 1) high school rank: 0.2098, 2) SAT-math: 0.1960, 3) SAT-verbal: 0.1385, 4) special entrance: 0.0566, 5) admission age: 0.0298. Predictors which remained significant when loaded into a multiple prediction equation are listed in order of predictive power with their incremental squared correlation coefficients: 1) high school class rank: 0.2098, 2) SAT-math: 0.0969, 3)admission age: 0.0421, 4) SAT- verbal: 0.0188. The total squared multiple correlation coefficient for the prediction equation was 0.3676. The equation correctly predicted 71.4% of the admission decisions (based on a 2.5 sophomore GPA). Double cross-validation resulted in an average acceptance prediction accuracy of 72.2%. The prediction equation reduced the error of prediction and was recommended for use.

acceptance rank, Technology, Education, Higher, teacher education