Proceedings of the International Conference on Emerging Intelligent Systems for Sustainable Development (ICEIS 2024)

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Data-Driven Decision Support System for Analyzing Student Engagement in Learning Analytics

Authors
Omar Talbi1, *, Abdelkader Ouared1
1Faculty of Mathematics and Computer Science, University of Tiaret, Tiaret, Algeria
*Corresponding author. Email: omar.talbi@univ-tiaret.dz
Corresponding Author
Omar Talbi
Available Online 31 August 2024.
DOI
10.2991/978-94-6463-496-9_27How to use a DOI?
Keywords
Learning Analytics; Data-Driven Decision Support System; Informal learning; Online Analytical Processing; Learning Record Store
Abstract

In the landscape of higher education, a significant portion of student learning occurs within digital environments, facilitated by interconnected networks such as Learning Management Systems (LMS), Massive Open Online Courses (MOOCs), and various online platforms. This digital landscape generates a vast repository of educational data, offering valuable insights for educational stakeholders. However, evaluating student engagement in online learning presents a critical challenge. This study addresses this challenge by focusing on the evaluation of student engagement using Learning Analytics (LA). We introduce DDS-Eng, a Data-Driven Decision Support System designed to analyze students’ engagement. Our approach involves thorough requirement analysis to define decision-makers’ needs and selected data sources, followed by the development of a multidimensional model capturing engagement aspects and associated metrics. We then implement a dedicated interface utilizing Online Analytical Processing (OLAP) queries and a Learning Analytics Dashboard (LAD) to analyze individual student behavior and overall student engagement comprehensively. Finally, we present an empirical evaluation of our LAD conducted in a controlled environment. This research underscores the importance of student engagement in online learning and emphasizes the need for innovative approaches to evaluate learner engagement in multimodal and informal learning environments.

Copyright
© 2024 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 Emerging Intelligent Systems for Sustainable Development (ICEIS 2024)
Series
Advances in Intelligent Systems Research
Publication Date
31 August 2024
ISBN
978-94-6463-496-9
ISSN
1951-6851
DOI
10.2991/978-94-6463-496-9_27How to use a DOI?
Copyright
© 2024 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  - Omar Talbi
AU  - Abdelkader Ouared
PY  - 2024
DA  - 2024/08/31
TI  - Data-Driven Decision Support System for Analyzing Student Engagement in Learning Analytics
BT  - Proceedings of the International Conference on Emerging Intelligent Systems for Sustainable Development (ICEIS 2024)
PB  - Atlantis Press
SP  - 357
EP  - 370
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-496-9_27
DO  - 10.2991/978-94-6463-496-9_27
ID  - Talbi2024
ER  -