Date of this Version
Wang, W. (2013). Testing the validity of GRE scores on predicting graduate performance for engineering students. M.A. thesis, University of Nebraska, Lincoln, NE.
The Graduate Record Examination (GRE), a set of standardized tests designed to determine the scholastic potential of graduate students, is widely used in graduate admissions in the United States. How GRE can predict graduate students’ performance has crucial importance both for universities and for students. Numerous of research studies have examined the validity of GRE scores in predicting graduate success, however, some limitations and gaps still existed in previous studies. This study targeted a specific discipline of engineering, and investigated the validity of GRE scores in predicting graduate performance, as measured by graduate GPA (GGPA) for engineering students. The differences in the validity of GRE scores between American and international students and between master’s and doctoral students were tested. The incremental predictive abilities of GRE over undergraduate GPA (UGPA) and TOEFL scores were also examined. Data of this study were obtained from 1083 students from the engineering programs in a large comprehensive midwestern university. Results of this study indicated that GRE was a useful predictor in predicting 1st-year, 2nd-year, and total GGPA of engineering students. The GRE-Verbal (GRE-V) and GRE-Quantitative (GRE-Q) scores had a different pattern in predicting graduate grades for master’s and doctoral students. The GRE-V and GRE-Q scores explained more variance in graduate performance for American students than for international students, but no statistically significant differences were found except when GRE-Q predicted GGPA total scores. UGPA was found to be a strong predictor, and TOEFL scores were also significantly correlated with the criterion variables. GRE scores were found to have significant incremental validity over UGPA and TOEFL scores in predicting graduate grades. These findings have implications for graduate admission decisions for engineering programs, and can suggest directions of future research, which were also discussed in this study.
Advisor: Kurt F. Geisinger