Proceedings of the E-Learning and Smart Engineering Systems (ELSES 2024)

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Utilizing Cloud Computing And DBSCAN For Personalized Online Learning

Authors
Ikram Amzil1, *, Souhaib Aammou2, Youssef Jdidou3, Hicham Er-Radi4
1Ecole Normale Supérieure, Abdelmalek Essaadi University, Tetuan, Morocco
2Ecole Normale Supérieure, Abdelmalek Essaadi University, Tetuan, Morocco
3Ecole Marocaine des Sciences de l‘Ingénieur, Laboratory of Intelligent Systems and Applications (LSIA), Tangier, Morocco
4Ecole Normale Supérieure, Abdelmalek Essaadi University, Tetuan, Morocco
*Corresponding author. Email: ikram.amzil@gmail.com
Corresponding Author
Ikram Amzil
Available Online 20 June 2025.
DOI
10.2991/978-2-38476-408-2_34How to use a DOI?
Keywords
Machine learning; DBSCAN; cloud computing; adaptive learning
Abstract

In this study, we introduce a Cloud-Supported Machine Learning System (CSMLS) designed to enhance the online learning experience for computer programming students. This system leverages unsupervised machine learning, specifically using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, in conjunction with a rule-based inference engine hosted on a cloud backend. The primary aim of CSMLS is to offer personalized, dynamic, and engaging learning support by analyzing and responding to various contextual factors affecting learners. These factors include background knowledge, timing, location, and the surrounding environment, all of which are dynamically captured from learners’ mobile devices. By focusing on these contextual elements, CSMLS aims to significantly improve the programming skills of learners by encouraging them to tackle practical, real-world coding challenges, thus maximizing their learning performance through tailored guidance.

Copyright
© 2025 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 E-Learning and Smart Engineering Systems (ELSES 2024)
Series
Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date
20 June 2025
ISBN
978-2-38476-408-2
ISSN
2667-128X
DOI
10.2991/978-2-38476-408-2_34How to use a DOI?
Copyright
© 2025 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  - Ikram Amzil
AU  - Souhaib Aammou
AU  - Youssef Jdidou
AU  - Hicham Er-Radi
PY  - 2025
DA  - 2025/06/20
TI  - Utilizing Cloud Computing And DBSCAN For Personalized Online Learning
BT  - Proceedings of the E-Learning and Smart Engineering Systems (ELSES 2024)
PB  - Atlantis Press
SP  - 485
EP  - 495
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-2-38476-408-2_34
DO  - 10.2991/978-2-38476-408-2_34
ID  - Amzil2025
ER  -