Scholastic Aptitude Test, Sex and Department as Predictors of University Academic Performance: The Case of Addis Ababa University

Abstract

The objective of the present study was to assess the predictive power of SAT, Sex and Department in AAU College of Science and Social Science. To analyse and interpret the collected data, both descriptive and inferential statistics were used. Pearson Product-Moment Correlation was employed to see the magnitude and direction of the relationship between the predictor variables and the criterion measure. To see the percentage of variance in students first year CGPA that can be explained by predictor variables multiple regression was used. Lastly, to identify relative contribution of predictor variables (or to identify the best predictor variable step-wise regression was employed. Predictor variables are statistically significant predictors of college academic performance for all participants 17.6% (R 2 =0.176, F (3, 296)=21.068, P<0.05). Regarding the gender, there is a significant difference between male and female students college academic performance. A large amount of variance accounted for was found for female students 22% (R 2 =0.220, F (2, 95)=13.362, P<0.05) than for males 13.2% (R 2 =0.132, F (2,199) =15.095, P<0.05). When the disciplines are considered, College of Science was found to be a more significantly predicted field of studies 17.5% (R 2 =0.175, F(3, 151)=10.697, P<0.05) than Social Science 8.4%(R 2 =0.084, F(3, 141)=4.317, P<0.05). Regarding the relative contribution of each predictor variables, the study result showed that department was the best predictor followed by SAT. Sex was a non-significant predictor of college CGPA. Hence, further investigation is required to conduct a study on the predictive power of sex.

The Influence of University Entrance Examination Results, Gender and Field of Study on Semester Cumulative Grade-point Averages (CGPAs) of First Year Students: The Case of Raya University

“…The third study variable, field of study was not found as statistically significant predictor to semester CGPA score. This result is different from the finding studied by Gobeze (2017), Scott-Clayton (2012) and Melaku (2014) cited in Desta (2017), who found field of study as statistically significant predictor to CGPA scores. This difference might be stemmed from the background of participants and the study have been taken from the newly emerged university, in which most of students assigned to the university had relatively lower than senior university students.…”

The Influence of University Entrance Examination Results, Gender and Field of Study on Semester Cumulative Grade-point Averages (CGPAs) of First Year Students: The Case of Raya University

“…The third study variable, field of study was not found as statistically significant predictor to semester CGPA score. This result is different from the finding studied by Gobeze (2017), Scott-Clayton (2012) and Melaku 2014cited in Desta 2017, who found field of study as statistically significant predictor to CGPA scores. This difference might be stemmed from the background of participants and the study have been taken from the newly emerged university, in which most of students assigned to the university had relatively lower than senior university students.…”

“…The second, statistically significant predictor variable to semester CGPA score, selected by stepwise multiple regression was university entrance exam results [ F(1,196)= 4.640, p<0.05]. The present result was similar with the findings of Aboma (2009), Desta (2017), Melaku's (2014) cited in Desta (2017), Gobeze (2017) and Yoseph (2014;.…”