Data-Driven Decision Support System for Analyzing Student Engagement in Learning Analytics
- 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.
Cite this article
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 -