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Authors: Laci Mary Barbosa Manhães 1 ; Sérgio Manuel Serra da Cruz 2 and Geraldo Zimbrão 1

Affiliations: 1 UFRJ, Brazil ; 2 UFRRJ, Brazil

ISBN: 978-989-758-022-2

ISSN: 2184-5026

Keyword(s): Educational Data Mining, Dropout Rate, Data Mining, Databases, Algorithms.

Related Ontology Subjects/Areas/Topics: Assessment and Accreditation of Courses and Institutions ; Authoring Tools and Content Development ; Computer-Supported Education ; Cooperation with Industry in Teaching ; e-Learning ; Information Technologies Supporting Learning ; Learning/Teaching Methodologies and Assessment ; Metrics and Performance Measurement ; Social Context and Learning Environments

Abstract: This paper uses educational data mining techniques to identify the variables that can help educational managers to detect students that present low performance or are in risk to dropout their undergraduate education. We investigated real world academic data of students of the largest Public Federal Brazilian University. We established three categories of students with different academic trajectory in order to investigate their performance and the dropout rates. This study shows that even analyzing three different classes of 14.000 students it was possible to have a global precision above 80% for several classification algorithms. The results of Naïve Bayes model were used to support the quantitative analysis. In this work, we stress that even few differences between the three classes of students that can be perceived on the basis of qualitative information.

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Paper citation in several formats:
Manhães, Laci Mary; Manuel Serra da Cruz, S. and Zimbrão, G. (2014). The Impact of High Dropout Rates in a Large Public Brazilian University - A Quantitative Approach Using Educational Data Mining.In Proceedings of the 6th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-022-2, ISSN 2184-5026, pages 124-129. DOI: 10.5220/0004958601240129

@conference{csedu14,
author={Manhães, Laci Mary and Sérgio Manuel Serra da Cruz. and Geraldo Zimbrão.},
title={The Impact of High Dropout Rates in a Large Public Brazilian University - A Quantitative Approach Using Educational Data Mining},
booktitle={Proceedings of the 6th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2014},
pages={124-129},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004958601240129},
isbn={978-989-758-022-2},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - The Impact of High Dropout Rates in a Large Public Brazilian University - A Quantitative Approach Using Educational Data Mining
SN - 978-989-758-022-2
AU - Manhães, Laci Mary
AU - Manuel Serra da Cruz, S.
AU - Zimbrão, G.
PY - 2014
SP - 124
EP - 129
DO - 10.5220/0004958601240129

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