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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1907

Title: Predicting Students’ Academic Performances – A Learning Analytics Approach using Multiple Linear Regression
Authors: Oyerinde, O. D.
Chia, P. A.
Keywords: Educational Data Mining
Issue Date: 2017
Publisher: International Journal of Computer Applications
Series/Report no.: Vol. 157;No. 4; Pp 37- 44
Abstract: Learning Analytics is an area of Information Systems research that integrates data analytics and data mining techniques with the aim of enhancing knowledge management and learning delivery in education management..The current research proposes a framework to administer prediction of Students Academic Performance using Learning Analytics techniques. The research illustrates how this model is used effectively on secondary data collected from the Department of Computer Science, University of Jos, Nigeria.Multiple Linear Regression was used with the aid of the Statistical Package for Social Sciences (SPSS) analysis tool. Statistical Hypothesis testing was then used to validate the model with a 5% level of significance.
URI: http://hdl.handle.net/123456789/1907
ISSN: 0975 – 8887
Appears in Collections:Computer Science

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