COMPARATIVE ANALYSIS OF ENGAGEMENT LEVELS AND PERFORMANCE USING CANVAS, MOODLE, AND BLENDED LEARNING IN SOUTH-SOUTH NIGERIAN UNIVERSITIES
This study examined students’ engagement levels and performance using the Canvas, Moodle, and blended learning approaches in South-South Nigerian universities. The study adopted a pre-test, post-test, non-randomized quasi-experimental design with a population of 2,873 undergraduate students. The multistage sampling procedure was used to obtain a sample size of 235 undergraduate students. The Learning Platform Self-Engagement Scale (LPSES) and Computer-in-Education Performance Test (CPT) were used to collect data. Experts duly validated these instruments, and the reliability coefficients of the instruments were obtained using Cronbach’s alpha and Kuder Richardson-21 (KR-21) formula, which yielded reliability coefficients of 0.84 and 0.87, respectively. The research questions were addressed using descriptive statistics of means and standard deviation, and the hypotheses were tested at the 0.05 level of significance using ANCOVA. The results showed that students who were taught Computer in education (CIE) concepts using the Canvas e-Learning platform, the Moodle e-Learning platform, and the blended learning approach did not significantly differ in their level of engagement. The study further revealed that the Moodle e-Learning platform had a more significant effect on students’ academic performance than the Canvas e-Learning platform and blended learning. The study concluded that digital learning platforms, specifically Canvas, Moodle, and other blended learning models, play a crucial role in shaping student engagement and academic performance in FUs in SSN. Therefore, it is recommended that lecturers should adopt instructional strategies that incorporate the Canvas and Moodle e-Learning platforms to teach CIE concepts in Federal Universities in South-South Nigeria (SSN).
Institutions
- University of Port Harcourt (NG)
- Rivers State University (NG)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-12-12
- DOI
- https://doi.org/10.5281/zenodo.17911493
- Primary Topic
- Online and Blended Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.00