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http://hdl.handle.net/20.500.12358/25066
TitleMining educational data to improve students' performance: a case study
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Abstract

Educational data mining concerns with developing methods for discovering knowledge from data that come from educational domain. In this paper we used educational data mining to improve graduate students’ performance, and overcome the problem of low grades of graduate students. In our case study we try to extract useful knowledge from graduate students data collected from the college of Science and Technology–Khanyounis. The data include fifteen years period [1993-2007]. After preprocessing the data, we applied data mining techniques to discover association, classification, clustering and outlier detection rules. In each of these four tasks, we present the extracted knowledge and describe its importance in educational domain.

Authors
Abu Tair, Mohammed M
El-Halees, Alaa M.
TypeJournal Article
Date2012
Subjects
educational data mining
classification
association rules; clustering
outlier detection
Published inInternational Journal of Information
SeriesVolume: 2, Number: 2
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  • Staff Publications- Faculty of Information Technology [192]
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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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