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

Mohammed Gobeze
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引用次数: 1

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% (R2=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% (R2=0.220, F (2, 95) =13.362, P<0.05) than for males 13.2% (R2=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%(R2=0.175, F(3, 151)=10.697, P<0.05) than Social Science 8.4% (R2=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.
以亚的斯亚贝巴大学为例:学业能力测试、性别和院系作为大学学业成绩的预测因素
本研究的目的是评估SAT、性别和院系在AAU理社学院的预测能力。为了分析和解释收集到的数据,使用了描述性和推断性统计。采用Pearson积差相关来观察预测变量与标准测量之间关系的大小和方向。为了观察学生第一年CGPA的方差百分比,可以用预测变量多元回归来解释。最后,为了确定预测变量的相对贡献(或确定最佳预测变量),采用逐步回归。预测变量对大学学业成绩的预测率为17.6% (R2=0.176, F (3,296) =21.068, P<0.05)。在性别上,男女大学生学业成绩存在显著差异。女生的方差占22% (R2=0.220, F (2,95) =13.362, P<0.05),男生的方差占13.2% (R2=0.132, F (2,199) =15.095, P<0.05)。当考虑学科时,理学院被预测为17.5%(R2=0.175, F(3,151)=10.697, P<0.05),而社会科学被预测为8.4% (R2=0.084, F(3,141)=4.317, P<0.05)。对于各预测变量的相对贡献,研究结果显示系系是最佳预测变量,其次是SAT,性别是大学CGPA的不显著预测变量。因此,需要对性别的预测能力进行进一步的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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