Early Identification of At-Risk Students in Online Education: A Deep Learning Approach to Predictive Modelling Cover

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Early Identification of At-Risk Students in Online Education: A Deep Learning Approach to Predictive Modelling

Business Systems Research Journal

Volume 16 (2025): Issue 2 (December 2025)

By: Lediana Shala Riza, Lejla Abazi Bexheti and Jovana Zoroja

Open Access

|Dec 2025

Authors

Lediana Shala Riza

ls31402@seeu.edu.mk

South East European University, Faculty of Contemporary Sciences and Technologies, North Macedonia

Lejla Abazi Bexheti

l.abazi@seeu.edu.mk

South East European University, Faculty of Contemporary Sciences and Technologies, North Macedonia

Jovana Zoroja

jzoroja@efzg.hr

Faculty of Economics and Business, University of Zagreb, Croatia

DOI: https://doi.org/10.2478/bsrj-2025-0019 | Journal eISSN: 1847-9375 | Journal ISSN: 1847-8344

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Language: English

Page range: 69 - 91

Submitted on: Jan 14, 2025

|

Accepted on: Aug 15, 2025

|

Published on: Dec 21, 2025

Published by: IRENET - Society for Advancing Innovation and Research in Economy

In partnership with: Paradigm Publishing Services

Publication frequency: 2 issues per year

Keywords:

student performance prediction,

online learning environments,

deep learning framework,

Related subjects:

Business and economics,

Business management,

Management, organization, corporate governance,

Business management, other,

Mathematics and statistics for economists,

© 2025 Lediana Shala Riza, Lejla Abazi Bexheti, Jovana Zoroja, published by IRENET - Society for Advancing Innovation and Research in Economy
This work is licensed under the Creative Commons Attribution 4.0 License.

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