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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/12201

Title: Accessing Individual Students Academic Performance Using Random Effect Analysis (Multilevel Analysis)
Authors: Owusu-Ansah, Emmanuel DeGraft Johnson
Amissah, Ekow Ewusi
Frempong, Nana Kena
Keywords: Random effect ·
Random intercept model ·
Random intercept and slope model ·
Standard deviation ·
Issue Date: 21-Sep-2016
Publisher: Springer
Citation: School of Mathematical Sciences, University of Science and Technology of China and Springer-Verlag Berlin Heidelberg 2016
Abstract: Sometimes, people with interest in measuring quality of education take into account level in academic performance and various associated factors. Usually, an average academic performance is an accustomed way of assessment; however, this study examines on individual basis different factors that might have an impact on the academic performance of undergraduate students. Data on the semester weighted average of class of 2012 mathematics students were acquired from the Quality Assurance and Planning Unit and the Examination Office of the Department of Mathematics, Kwame Nkrumah University of Science and Technology. The main factors considered for this research were entry age, gender, entry aggregate, Ghana education service graded level of senior high school attended and geographical location. The statistical method considered was random effect. Since the interaction or variation around the slope was highly insignificant, the random intercept model was the better alternative ahead of the random intercept and slope model. Statistically, not all the parameter estimates are significant at α = 0.05 level of significance. It was observed that the difference in geographical location was not significant in the main effect model. Hence where a student comes from has no influence on their academic performance. However, entry aggregate, entry age and gender were all significant. Nevertheless, the geographical location with regard to the Northern Belt was significant in the linear trend with a standard deviation of approximately 0.712.
Description: An article published by Springer and also available at DOI 10.1007/s40304-016-0089-y
URI: http://hdl.handle.net/123456789/12201
Appears in Collections:College of Science

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