American Journal of Educational Research
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American Journal of Educational Research. 2014, 2(9), 713-726
DOI: 10.12691/education-2-9-3
Open AccessArticle

Contributions from Data Mining to Study Academic Performance of Students of a Tertiary Institute

David L. la Red Martínez1, 2, and Carlos E. Podestá Gómez3

1Departamento de Informática, Universidad Nacional del Nordeste, Corrientes, Argentina

2Departamento de ISI, Universidad Tecnológica Nacional, Resistencia, Argentina

3Departamento de Informática, Instituto Superior Curuzú Cuatiá, Curuzú Cuatiá, Argentina

Pub. Date: August 17, 2014

Cite this paper:
David L. la Red Martínez and Carlos E. Podestá Gómez. Contributions from Data Mining to Study Academic Performance of Students of a Tertiary Institute. American Journal of Educational Research. 2014; 2(9):713-726. doi: 10.12691/education-2-9-3

Abstract

Education-oriented data mining allows to predict determined type of factor or characteristic of a case, phenomenon or situation. In this article the mining models used are described and the main results are discussed. Mining models of clustering, classification and association are considered especially. In all cases seeks to determine patterns of academic success and failure for students, thus predicting the likelihood of dropping them or having poor academic performance, with the advantage of being able to do it early, allowing addressing action to reverse this situation. This work was done in 2013 with information on the years 2009 to 2013, students of the subject Operating Systems tertiary career Superior Technical Analyst (TSAP) Higher Institute of Curuzú Cuatiá (ISCC), Corrientes, Argentina.

Keywords:
academic performance data mining profiling students

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