Determinants of E-Learning Adoption among Students in Sierra Leone's Public Tertiary Institutions: A Cross-Institutional Survey of Digital Readiness, Communal Learning Preferences, and Platform Fit
DOI:
https://doi.org/10.68050/JAMS.2026.706Keywords:
e-learning adoption; communal learning orientation; platform fit; digital readiness; Sierra LeoneAbstract
The global COVID-19 pandemic has forced Higher Education (HE) institutions to undergo a digital transformation that has reshaped their operations and made online learning platforms a necessity instead of a luxury. The adoption of e-learning is not uniform in Sierra Leone where seven public tertiary institutions have more than 40,000 students. Learners often use the resources provided for the course, but do not use interactive and collaborative resources very often. This partial adoption brings up important questions relating to how certain student behaviors are connected to the use of e-learning platforms, and why adoption levels may differ in various institutional contexts. This study investigates adoption factors of e-learning from students' perspectives in public tertiary institutions in Sierra Leone, which includes digital readiness, communal learning orientation and platform fit. The study combines existing technology acceptance factors with culturally-based constructs and context factors. The design of the study used was cross-sectional with 1100 undergraduate students from seven institutions. Hypothesized relations were tested by using partial least squares structural equation modelling. The results indicate that communal learning orientation had a significant total direct effect on e-learning adoption, and this effect was partially mediated by platform fit which accounted for 51.9% of the total effect. The results indicated that there were significant differences between the groups, with perceived usefulness being the most important at the institutions that had partial implementation of LMS, the facilitating conditions at the institutions where infrastructure was limited, and the digital readiness at the polytechnic. The study has both theoretical and practical implications, as it offers a possible mediating mechanism (platform fit), and evidence for differentiated intervention frameworks, and methodological implications by operationalizing communal learning orientation as a measurable construct.
References
1. Bangura, M. (2024). Sociology of e-learning: A social observational trek at universities in Freetown, Sierra Leone. European Journal of Contemporary Education and E-Learning, 2(1), 193–207.
https://doi.org/10.59324/ejceel.2024.2(1).16
2. Boateng, R., Mbrokoh, A. S., Boateng, L., Senyo, P. K., & Ansong, E. (2016). Determinants of e-learning adoption among students of developing countries. The International Journal of Information and Learning Technology, 33(4), 248–262. https://doi.org/10.1108/IJILT-02-2016-0008
3. Cochran, W. G. (1977). Sampling techniques (3rd ed.). John Wiley & Sons.
4. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
5. Creswell, J. W., & Creswell, J. D. (2023). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE Publications.
6. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
7. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). SAGE Publications.
8. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
9. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.
https://doi.org/10.1080/10705519909540118
10. Learning Passport. (2025). How Sierra Leone integrated learners' needs into its National Digital Learning Strategy. https://www.learningpassport.org/stories/how-sierra-leone-integrated-learners-needs-its-national-digital-learning-strategy
11. Ngubane, N. I., & Makua, M. (2021). Intersection of Ubuntu pedagogy and social justice: Transforming South African higher education. Transformation in Higher Education, 6, Article a134. https://doi.org/10.4102/the.v6i0.113
12. Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
13. Sawaneh, I. A., Sesay, B., Mansaray, S. S., Koroma, M., & Inthavong, P. (2024). Assessing the impact of e-learning adoption on learning behavior in Sierra Leonean higher education. Asian Journal of Education and Social Studies, 50(5), 66–84. https://doi.org/10.9734/ajess/2024/v50i51342
14. Singh, R., Singh, S. K., & Mishra, N. (2024). Influence of e-learning on the students of higher education in the digital era: A systematic literature review. Education and Information Technologies, 29(15), 20201–20221. https://doi.org/10.1007/s10639-024-12604-4
15. Suliman, Z., Mohale, N. E., Maphoto, K. B., & Sevnarayan, K. (2024). The interconnectedness between Ubuntu principles and generative artificial intelligence in distance higher education institutions. Discover Education, 3, Article 188. https://doi.org/10.1007/s44217-024-00289-2
16. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
17. Waziri, N., Mufti, A., Ramesh Vasudevan, S., Beoku-Betts, I., & Oyedele, O. (2025). Sierra Leone Digital Learning Landscape Analysis: Developing the National Digital Learning Strategy (No. 175). EdTech Hub. https://docs.edtechhub.org/lib/66FHF97GN
18. Zheng, H., Han, F., Huang, Y., Wu, Y., & Wu, X. (2025). Factors influencing behavioral intention to use e-learning in higher education during the COVID-19 pandemic: A meta-analytic review based on the UTAUT2 model. Education and Information Technologies, 30(9), 12015–12053.
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