Machine Learning model for student drop-out prediction based on student engagement
Conference paper
Brezočnik, L., Nalli, G., De Leone, R., Val, S., Podgorelec, V. and Karakatič, S. 2023. Machine Learning model for student drop-out prediction based on student engagement. Karabegovic, I., Kovačević, A. and Mandzuka, S. (ed.) 9th International Conference on New Technologies, Development and Application. Sarajevo, Bosnia and Herzegovina 22 - 24 Jun 2023 Cham Springer. pp. 486–496 https://doi.org/10.1007/978-3-031-31066-9_54
| Type | Conference paper |
|---|---|
| Title | Machine Learning model for student drop-out prediction based on student engagement |
| Authors | Brezočnik, L., Nalli, G., De Leone, R., Val, S., Podgorelec, V. and Karakatič, S. |
| Abstract | Nowadays, the issue of student drop-out is addressed not only through the prism of pedagogy, but also by technological practices. In this paper, we demonstrate how a student drop-out could be predicted through a student’s performance using different Machine Learning techniques, i.e., supervised learning and unsupervised learning. The results show that various types of student engagement are essential factors in predicting drop-out and the final ECTS points achievements. |
| Sustainable Development Goals | 4 Quality education |
| Middlesex University Theme | Creativity, Culture & Enterprise |
| Conference | 9th International Conference on New Technologies, Development and Application |
| Page range | 486–496 |
| Proceedings Title | New Technologies, Development and Application VI: Volume 1 |
| Series | Lecture Notes in Networks and Systems |
| Editors | Karabegovic, I., Kovačević, A. and Mandzuka, S. |
| ISSN | 2367-3370 |
| Electronic | 2367-3389 |
| ISBN | |
| Paperback | 9783031310652 |
| Electronic | 9783031310669 |
| Publisher | Springer |
| Place of publication | Cham |
| Publication dates | |
| Online | 20 May 2023 |
| 20 May 2023 | |
| Publication process dates | |
| Accepted | 2023 |
| Deposited | 14 Jun 2024 |
| Output status | Published |
| Accepted author manuscript | File Access Level Open |
| Copyright Statement | This version of the paper has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-ma...), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-031-31066-9_54 |
| Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-031-31066-9_54 |
| Web address (URL) of conference proceedings | https://doi.org/10.1007/978-3-031-31066-9 |
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