This study explores how year-level progression influences students’ engagement with the Learning Management System (LMS) at the University of Cape Coast (UCC). It examines usage patterns across academic levels, the relationship between LMS engagement and academic performance, and barriers to effective LMS utilization. Using time-series analysis, linear regression, correlation analysis, and factor analysis, the study provides a nuanced understanding of LMS engagement dynamics. Findings reveal a progressive increase in LMS usage from first-year to final-year students, with final-year students demonstrating the highest and most consistent engagement due to their reliance on LMS for advanced academic tasks. First-year students, however, face adaptation challenges, resulting in sporadic usage. While year-level progression significantly influences LMS engagement (R = 0.621), academic performance and credit hours completed showed weak correlations with LMS utilization (r = 0.082, p > 0.05), suggesting that other factors contribute more directly to academic success. Barriers to LMS usage were categorized into three main components: inadequate infrastructure and high data costs (40.3%), insufficient institutional support (13.5%), and usability and device accessibility challenges (10.1%). The findings highlight critical policy implications. They call for targeted interventions like digital literacy training for first-year students, strengthened LMS infrastructure to ensure equitable access, and tailored resource allocation for advanced academic needs. Recommendations include partnering with internet service providers to subsidize data costs, enhancing technical and academic support systems, and introducing specialized LMS features for final-year students. The study concludes that while LMS plays a pivotal role in academic engagement, its effective utilization depends on addressing infrastructural, institutional, and user-specific barriers. By implementing the proposed measures, UCC can optimize LMS functionality, enhance student engagement, and support academic success across all levels, providing a model for other higher education institutions.
References
[1]
Abdul-Gafaar, S., Nyaaba, R. A., Anechana, R., & Anhwere, D. K. (2024). Exploring Cognitive Dissonance among Undergraduate Students at the University of Cape Coast: Investigating Resistance and Acceptance in the Adoption of Technology. Creative Education, 15, 2499-2520. https://doi.org/10.4236/ce.2024.1512152
[2]
Acheampong, A., & Fosu, M. (2020). Exploring Student Engagement with Learning Management Systems in Ghanaian Universities: A Case of UCC. Journal of Educational Technology, 19, 45-58. https://doi.org/10.1016/j.chb.2019.08.004
[3]
Adarkwah, M. A. (2021). “I’m Not against Online Teaching, but What about Us?”: ICT in Ghana Post Covid-19. Education and Information Technologies, 26, 1665-1685. https://doi.org/10.1007/s10639-020-10331-z
[4]
Ahmad, S., Mohd Noor, A. S., Alwan, A. A., Gulzar, Y., Khan, W. Z., & Reegu, F. A. (2023). Elearning Acceptance and Adoption Challenges in Higher Education. Sustainability, 15, Article 6190. https://doi.org/10.3390/su15076190
[5]
Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating E-Learning Systems Success: An Empirical Study. Computers in Human Behavior, 102, 67-86. https://doi.org/10.1016/j.chb.2019.08.004
[6]
Aljohani, M. (2017). Principles of “Constructivism” in Foreign Language Teaching. Journal of Literature and Art Studies, 7, 97-107.
[7]
Almarashdeh, I., Al-Saedi, A., & Al-Ghamdi, A. (2019). Impact of E-Learning on Students’ Academic Achievement in Higher Education. Educational Technology & Society, 22, 81-92.
[8]
Asare, R., Agyemang, G., & Abubakar, M. (2021). Challenges of E-Learning Adoption in Ghanaian Universities: A Case Study of University of Cape Coast. Journal of Educational Technology Development, 9, 45-59.
[9]
Ashrafi, A., Zareravasan, A., Rabiee Savoji, S., & Amani, M. (2022). Exploring Factors Influencing Students’ Continuance Intention to Use the Learning Management System (LMS): A Multi-Perspective Framework. Interactive Learning Environments, 30, 1475-1497. https://doi.org/10.1080/10494820.2020.1734028
[10]
Babbie, E. R. (2020). The Practice of Social Research. Cengage Learning.
[11]
Bolliger, D. U., & Martin, F. (2021). Engagement Matters: Student Perceptions on the Importance of Engagement Strategies in the Online Learning Environment. Online Learning, 25, 36-55.
[12]
Chou, P. N., Chang, L. C., & Chou, C. H. (2020). The Effects of Learning Management System on College Students’ Learning Performance and Engagement. International Journal of Educational Research, 102, Article 101592.
[13]
Cochrane, T., Keegan, T., & O’Leary, S. (2020). The Digital Transformation of Education: A Global Overview. Educational Media International, 57, 1-15.
[14]
Creswell, J. W., & Poth, C. N. (2016). Qualitative Inquiry and Research Design: Choosing among Five Approaches. Sage Publications.
[15]
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13, 319-340. https://doi.org/10.2307/249008
[16]
Dawson, S., Joksimovic, S., Poquet, O., & Siemens, G. (2019). Increasing the Impact of Learning Analytics. In Proceedings of the 9th International Conference on Learning Analytics & Knowledge (pp. 446-455).
Gok, K., Ozel, E., & Tok, M. (2019). Exploring Student Engagement with the Learning Management System. Journal of Educational Computing Research, 57, 1747-1764.
[19]
Heo, J., & Han, S. (2021). Effects of Collaborative Learning and Self-Regulated Learning on Students’ Engagement in Higher Education. Educational Technology Research and Development, 69, 2065-2086.
[20]
Jonassen, D. H., & Land, S. M. (2012). Theoretical Foundations of Learning Environments (2nd ed.). Routledge.
[21]
Khan, M. A., Nabi, M. K., Khojah, M., & Tahir, M. (2020). Students’ Perception towards E-Learning during COVID-19 Pandemic in India: An Empirical Study. Sustainability, 13, 57.
[22]
Kintu, M. J., Zhu, C., & Kagambe, E. (2020). Blended Learning Effectiveness: The Relationship between Student Characteristics, Design Features, and Outcomes. International Journal of Educational Technology in Higher Education, 17, 1-23.
[23]
Kumar, J. A. (2021). Educational Chatbots for Project-Based Learning: Investigating Learning Outcomes for a Team-Based Design Course. International Journal of Educational Technology in Higher Education, 18, Article No. 65. https://doi.org/10.1186/s41239-021-00302-w
[24]
Makokha, G. L., & Mutisya, D. N. (2019). Status of E-Learning in Public Universities in Kenya. International Review of Research in Open and Distributed Learning, 20, 170-187.
[25]
Mohammadi, M. K., Mohibbi, A. A., & Hedayati, M. H. (2021). Investigating the Challenges and Factors Influencing the Use of the Learning Management System during the Covid-19 Pandemic in Afghanistan. Education and Information Technologies, 26, 5165-5198. https://doi.org/10.1007/s10639-021-10517-z
[26]
Panadero, E. (2017). A Review of Self-Regulated Learning: Six Models and Four Directions for Research. Frontiers in Psychology, 8, Article 422. https://doi.org/10.3389/fpsyg.2017.00422
[27]
Porter, W. W., Graham, C. R., Bodily, R. G., & Sandberg, D. S. (2016). A Qualitative Analysis of Institutional Drivers and Barriers to Blended Learning Adoption in Higher Education. The Internet and Higher Education, 28, 17-27. https://doi.org/10.1016/j.iheduc.2015.08.003
[28]
Rienties, B., Toetenel, L., & Bryan, J. (2020). The Role of Learning Analytics in Understanding and Enhancing the Student Experience. Computers & Education, 146, Article 103739.
[29]
Selwyn, N. (2010). Looking Beyond Learning: Notes Towards the Critical Study of Educational Technology. Journal of Computer Assisted Learning, 26, 65-73. https://doi.org/10.1111/j.1365-2729.2009.00338.x
[30]
Shadat, M., Rahman, M., & Samy, M. (2021). Adoption of LMS in Developing Countries: A Critical Review. Journal of E-Learning, 15, 35-48.
[31]
Ssekakubo, G., Ochieng, D., & Byamugisha, A. (2020). E-Learning in Uganda: A Study of University Students’ Experiences. International Journal of Education and Development using Information and Communication Technology, 16, 58-74.
[32]
Sung, Y. T., Chang, K. E., & Liu, T. C. (2020). The Effects of Integrating Mobile Devices with Teaching and Learning on Students’ Learning Performance: A Meta-Analysis and Research Synthesis. Computers & Education, 94, 252-275.
[33]
Venkatesh, V., Thong, J., & Xu, X. (2016). Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead. Journal of the Association for Information Systems, 17, 328-376. https://doi.org/10.17705/1jais.00428
[34]
Wang, Y., Han, X., & Yang, J. (2020). Revisiting the Blended Learning Literature: Using a Complex Adaptive Systems Framework. Educational Technology & Society, 23, 1-23.
[35]
Zimmerman, B. J. (2002). Becoming a Self-Regulated Learner: An Overview. Theory Into Practice, 41, 64-70. https://doi.org/10.1207/s15430421tip4102_2
[36]
Zimmerman, B. J., & Schunk, D. H. (2011). Self-Regulated Learning and Academic Achievement: Theoretical Perspectives (2nd ed.). Routledge.
