Proceedings of the International Conference on Intelligent Data Analysis and Applications (IDAA 2025)

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Predicting the Impact of Part-Time Employment on Academic Performance among University Students in Bangladesh Using Machine Learning Models

Authors
MD. Ariful Islam1, Firoz Hasan1, *, MST Israt Jahan Shifa1, Md. Awal Hadi1, Mohammad Obaidur Rahman2
1Department of Computer Science and Engineering, Daffodil International University (DIU), Dhaka, Bangladesh
2Department of Computer Science and Engineering, Chittagong University of Engineering and Technology (CUET), Chittagong, Bangladesh
*Corresponding author. Email: firoz.cse@diu.edu.bd
Corresponding Author
Firoz Hasan
Available Online 8 June 2026.
DOI
10.2991/978-94-6239-664-7_95How to use a DOI?
Keywords
Part-time job; academic performance; CGPA; working hour; machine learning
Abstract

This study in Bangladesh is a more detailed analysis of how part time jobs affect Street CGPA of the students. The survey involved 611 Small-Island State respondents that included influences on employment type, % of average time per day spent and others differences. The research focuses on the nexus between students’ work hours and their CGPA. The data will be analyzed using cutting-edge machine learning methodologies Decision Tree, Random Forest and Gradient Boosting etc. The significant factors in predicting academic performance were tested by chi-square statistics to assess feature importance. Results are discussed in terms of the comparison between models along accuracy, precisions, recall and overall balance analyses and therefore robustness across results. The results offer implications for the policy makers, educators and students about effect of part-time job on school performance in terms of how to meet a sufficient balance between work and study.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Intelligent Data Analysis and Applications (IDAA 2025)
Series
Advances in Intelligent Systems Research
Publication Date
8 June 2026
ISBN
978-94-6239-664-7
ISSN
1951-6851
DOI
10.2991/978-94-6239-664-7_95How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - MD. Ariful Islam
AU  - Firoz Hasan
AU  - MST Israt Jahan Shifa
AU  - Md. Awal Hadi
AU  - Mohammad Obaidur Rahman
PY  - 2026
DA  - 2026/06/08
TI  - Predicting the Impact of Part-Time Employment on Academic Performance among University Students in Bangladesh Using Machine Learning Models
BT  - Proceedings of the International Conference on Intelligent Data Analysis and Applications (IDAA 2025)
PB  - Atlantis Press
SP  - 1408
EP  - 1421
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-664-7_95
DO  - 10.2991/978-94-6239-664-7_95
ID  - Islam2026
ER  -