Year: 2024
Type: book-chapter
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.
Authors: Omar Talbi, Abdelkader Ouared
Institution: Université IBN Khaldoun Tiaret
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4402009455