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Authors: Horea Greblă 1 ; Cătălin V. Rusu 1 ; 2 ; Adrian Sterca 1 ; Darius Bufnea 1 and Virginia Niculescu 1

Affiliations: 1 Department of Computer-Science, Babeş-Bolyai University, Romania ; 2 Institute for German Studies, Babeş-Bolyai University, Romania

Keyword(s): Recommendation Systems, Machine Learning, Neural Networks, Academic Assessment.

Abstract: The purpose of this work is to study the possible approaches to build a recommendation system that could help students in organizing their work and improving their results. More specifically, we intend to predict grades of a student for future exams, based on his/her previous results and the past grades received by all students from the same series/group. We have tried several machine learning methods for predicting future student grades, and finally we obtained good results, namely a mean absolute prediction error smaller than 1. The best variant proved to be the one based on neural networks that leads to a mean absolute prediction error smaller than 0.5. These results show the practical applicability of our proposed methodology, and consequently, we built, based on these, a practical recommendation system available to students as a web application.

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Paper citation in several formats:
Greblă, H.; Rusu, C.; Sterca, A.; Bufnea, D. and Niculescu, V. (2022). Recommendation System for Student Academic Progress. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-547-0; ISSN 2184-433X, SciTePress, pages 285-292. DOI: 10.5220/0010816300003116

@conference{icaart22,
author={Horea Greblă. and Cătălin V. Rusu. and Adrian Sterca. and Darius Bufnea. and Virginia Niculescu.},
title={Recommendation System for Student Academic Progress},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2022},
pages={285-292},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010816300003116},
isbn={978-989-758-547-0},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Recommendation System for Student Academic Progress
SN - 978-989-758-547-0
IS - 2184-433X
AU - Greblă, H.
AU - Rusu, C.
AU - Sterca, A.
AU - Bufnea, D.
AU - Niculescu, V.
PY - 2022
SP - 285
EP - 292
DO - 10.5220/0010816300003116
PB - SciTePress

- Science and Technology Publications, Lda.
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