Prediction in Pre-University Education System Using Machine Learning Methods

Ioan-Daniel Pop

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Paper

Prediction in Pre-University Education System Using Machine Learning Methods

Topics: Data Mining; Deep Learning; Machine Learning; Neural Networks

In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, 430-437, 2024 , Rome, Italy

Author: Ioan-Daniel Pop

Affiliation: “Babes-Bolyai” University, Department of Computer Science, 400084, Cluj-Napoca, Romania

Keyword(s): Educational Data Mining, Regression, Classification, Performance Prediction, Artificial Neural Network, Random Forest.

Abstract: This paper aims to present the results obtained from the experiments of predicting the academic performance of students from the pre-university education system in Romania. The prediction of academic performance is an extremely important topic in the field of educational data mining, the creation of such a system bringing many benefits to the teaching-learning-evaluation process. The data set used in this paper is original and contains real data collected from 24 educational institutions in the Romanian rural and urban environment. The sample is composed of students who belong to all social categories and who had different academic performances. The results obtained for Random Forest and Artificial Neural Network were good, more precisely following the experiments performed, it resulted in an accuracy greater than 90%.

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Paper citation in several formats:

Pop, I. (2024). Prediction in Pre-University Education System Using Machine Learning Methods. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4; ISSN 2184-433X, SciTePress, pages 430-437. DOI: 10.5220/0012356900003636

@conference{icaart24,
author={Ioan{-}Daniel Pop.},
title={Prediction in Pre-University Education System Using Machine Learning Methods},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={430-437},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012356900003636},
isbn={978-989-758-680-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Prediction in Pre-University Education System Using Machine Learning Methods
SN - 978-989-758-680-4
IS - 2184-433X
AU - Pop, I.
PY - 2024
SP - 430
EP - 437
DO - 10.5220/0012356900003636
PB - SciTePress