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Authors: Daiane Rodrigues ; Murilo S. Regio ; Soraia R. Musse and Isabel H. Manssour

Affiliation: Pontifical Catholic University of Rio Grande do Sul, PUCRS, School of Technology, Porto Alegre, RS, Brazil

Keyword(s): Educational Data Mining, Students’ Performance, National Exam Education, Logistic Regression.

Abstract: The High School National Exam (ENEM) is the major Brazilian exam to measure the knowledge of high school students. Since it is also used as a criterion to enter public and private universities, there is an interest in identifying the indicators that have the most influence in obtaining good performance. This work presents a prediction model for the participant’s performance, which allows us to identify the features that best explain their exam results. For this work, we used open data provided by the Ministry of Education and the Logistic Regression technique. The predictive model allows us to infer the student’s performance with an accuracy of 74%. Also, since we are using a statistical model of easy interpretation and implementation, instead of a complex Machine Learning technique, school managers could use the results without a deep understanding of the used mining technique.

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Paper citation in several formats:
Rodrigues, D.; Regio, M.; Musse, S. and Manssour, I. (2021). Data Mining on the Prediction of Student’s Performance at the High School National Examination. In Proceedings of the 13th International Conference on Computer Supported Education - Volume 1: CSEDU; ISBN 978-989-758-502-9; ISSN 2184-5026, SciTePress, pages 92-99. DOI: 10.5220/0010408000920099

@conference{csedu21,
author={Daiane Rodrigues. and Murilo S. Regio. and Soraia R. Musse. and Isabel H. Manssour.},
title={Data Mining on the Prediction of Student’s Performance at the High School National Examination},
booktitle={Proceedings of the 13th International Conference on Computer Supported Education - Volume 1: CSEDU},
year={2021},
pages={92-99},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010408000920099},
isbn={978-989-758-502-9},
issn={2184-5026},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Computer Supported Education - Volume 1: CSEDU
TI - Data Mining on the Prediction of Student’s Performance at the High School National Examination
SN - 978-989-758-502-9
IS - 2184-5026
AU - Rodrigues, D.
AU - Regio, M.
AU - Musse, S.
AU - Manssour, I.
PY - 2021
SP - 92
EP - 99
DO - 10.5220/0010408000920099
PB - SciTePress

- Science and Technology Publications, Lda.
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