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A Data-Driven Exploration of Factors Affecting Student Performance in a Third-Level Institution

ARAN - Access to Research at NUI Galway

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dc.contributor.author Madden, Michael G. en
dc.contributor.author Lyons, William en
dc.contributor.author Kavanagh, Ita en
dc.date.accessioned 2009-05-22T09:41:22Z en
dc.date.available 2009-05-22T09:41:22Z en
dc.date.issued 2008 en
dc.identifier.uri http://hdl.handle.net/10379/202 en
dc.description.abstract This paper describes an application of data mining techniques to the analysis of student academic records, collected at Limerick Institute of Technology, with the goal of acquiring clearer, evidence-based understanding of how a variety factors affect students' examination performance. To this end, a comprehensive dataset has been prepared. It has been analysed using a variety of machine learning/data mining techniques, in order to examine it from multiple perspectives. Of the techniques used, Bayesian networks have been found to be best in terms of yielding results that are comprehensible and meaningful. The results of this work provide a useful snapshot of factors affecting performance for the student group analysed, as well as demonstrating a process by which other institutions may analyse their own student groups. en
dc.format application/pdf en
dc.language.iso en en
dc.subject Data mining en
dc.subject Bayesian networks en
dc.subject Third level institutions en
dc.subject Student performance en
dc.subject.lcsh Bayesian statistical decision theory -- Data processing en
dc.subject.lcsh Education, Higher en
dc.subject.lcsh Academic achievement en
dc.subject.lcsh Data mining en
dc.title A Data-Driven Exploration of Factors Affecting Student Performance in a Third-Level Institution en
dc.type Conference Paper en

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