HIDDEN OPPORTUNITIES IN THE PREDICTION OF COLLEGE GRADES FOR DIFFERENT SUBGROUPS

The purpose of this paper was to examine the problems and opportunities of academic prediction for different ethnic groups. Several recent studies of academic prediction for blacks and whites were reviewed in regard to: 1) the situation in which the data were obtained; 2) the prediction technique employed, and 3) the data distribution likely to give rise to the obtained prediction indices. It was suggested that a total-group regression equation which "benefits" a minority group by overpredicting mean grade may actually be very disadvantageous if accompanied by a large error of estimate. The damage can be produced by precluding selection of the most qualified minority group members and thus lowering the groups' performance. Differential process theory was proposed as a potential source of explanations for differential prediction. It was proposed that alternative strategic approaches to scholastic tasks might alter the covariance of predictor tests with grades. Finally, it was suggested that, under certain circumstances, the patterns of standardized regression weights in the prediction of grades, might suggest group difference in problem-solving strategies.     

WHAT SIZE SAMPLES FOR METHODS/MATERIALS EXPERIMENTS?

Careful planning of educational experiments includes decisions about the sample size to be used. This paper provides a guide to the minimum size of treatment groups, inferred from the relationships between pupil norms and norms for class averages of standardized achievement tests. With "highly effective" treatments and simple random assignment of subjects to conditions, 60 to 85 subjects is derived as the minimum number per group. With "moderately effective" treatments, the minimum number is 235 or more. Use of stratified samples reduces the minimum by fifteen to forty percent.