Monitoring Collaborative Interactions in Online Learning: Insights from Moodle Log Records
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| Title: | Monitoring Collaborative Interactions in Online Learning: Insights from Moodle Log Records |
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| Language: | English |
| Authors: | Anuradha Peramunugamage (ORCID |
| Source: | Journal of Learning for Development. 2025 12(2):290-312. |
| Availability: | Commonwealth of Learning. 4710 Kingsway Suite 2500, Burnaby, BC V5H 4M2 Canada. Tel: 604-775-8200; Fax: 604-775-8210; e-mail: jl4d@col.org; Web site: http://www.col.org |
| Peer Reviewed: | Y |
| Page Count: | 23 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Cooperative Learning, Interaction, Electronic Learning, Learning Management Systems, Learning Analytics, Computer Mediated Communication, Assignments, Workshops, College Students, Academic Achievement, Learning Activities |
| ISSN: | 2311-1550 |
| Abstract: | Interactions among students in online learning environments are difficult to monitor but can be crucial for their academic performance. Moodle is one of the best and most popular online learning platforms, where its log records can reveal important information on students' engagement and the respective performance. This study examines the degree of student participation and performance in online collaborative content creation activities, based on three iterative testing cycles: systematically designed Moodle forum discussions, group assignments, Wikis and Moodle workshops, specifically to obtain peer feedback. The abovementioned collaborative Moodle content creation and corresponding log record analysis was executed for four modules conducted at two higher education institutions from Sri Lanka and Brazil. Regression analysis on log records and student performance on four modules indicated a positive correlation, with R2 values between 26% and 43.8%. A significant amount of data which remained unexplained were subjected to the Vector Space Model (VSM) data mining algorithm to uncover in-depth information. The results, indicating substantial influence on student performance by participation in online collaborative activities, provided vital insights into necessary improvements on instructional design. Accordingly, promoting productive student interactions could be significant in online learning environments, and the findings of this study underscore the importance of utilising the learning analytics data driven approaches to elevate student performance. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1480621 |
| Database: | ERIC |
| Abstract: | Interactions among students in online learning environments are difficult to monitor but can be crucial for their academic performance. Moodle is one of the best and most popular online learning platforms, where its log records can reveal important information on students' engagement and the respective performance. This study examines the degree of student participation and performance in online collaborative content creation activities, based on three iterative testing cycles: systematically designed Moodle forum discussions, group assignments, Wikis and Moodle workshops, specifically to obtain peer feedback. The abovementioned collaborative Moodle content creation and corresponding log record analysis was executed for four modules conducted at two higher education institutions from Sri Lanka and Brazil. Regression analysis on log records and student performance on four modules indicated a positive correlation, with R2 values between 26% and 43.8%. A significant amount of data which remained unexplained were subjected to the Vector Space Model (VSM) data mining algorithm to uncover in-depth information. The results, indicating substantial influence on student performance by participation in online collaborative activities, provided vital insights into necessary improvements on instructional design. Accordingly, promoting productive student interactions could be significant in online learning environments, and the findings of this study underscore the importance of utilising the learning analytics data driven approaches to elevate student performance. |
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| ISSN: | 2311-1550 |
