Date of Award

2005

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Curriculum, Instruction, and Media Technology

Abstract

This was a quantitative method research study that looked at conditionally-admitted students at Indiana State University, a mid-sized public institution. The study's purpose was to find factors that could be used to predict the success of conditionally-admitted students. Quantitative analyses tested the predictive capability of a combination of eight cognitive and non-cognitive variables, some that have traditionally been used to predict success in college (high school grade point average, high school class rank, standardized test scores) and some that have not (motivation, attitude, gender, ethnicity, and geographic region). The study's eight variables together accounted for 14% of the variance in conditionally-admitted students' 1 st semester grade point average. The independent variable SAT score was the only significant contributor to the prediction of 1 st semester grade point average. Based on the correlation statistics, the ANOVA results, and the results of the multiple regression analyses the number of predictor variables was reduced to two, high school grade point average and SAT score, and the analyses were run again in an effort to find a significant predictive model. The two variables accounted for 7.7% of the variance in conditionally-admitted students' 1 st semester grade point average, and both variables were significant contributors to the prediction model. While it had been hoped to find a combination of traditional and non-traditional factors that were predictors of conditionally-admitted student success, the results of this study showed that of the eight variables, the traditionally used factors of high school grade point average and SAT score were the best predictors in this instance.

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