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Abstract
To foster the continuity of learning for Higher Education Institutions (HEIs) during the COVID-19 pandemic, the Uganda National Council of Higher Education approved Emergency Open Distance and eLearning (ODeL). Clarke International University (CIU) was among the first HEIs to receive approval. This survey aimed to evaluate the ease of maneuvering on the e-learning platform at the CIU. A cross-sectional study was conducted to survey 485 students between December 2020 and January 2021. Of the 485 participants, 79.8% (387) maneuvered quickly through the e-learning platform. The odds of maneuvering through the E-learning platform increased with Information Communication Technology (ICT) and E-Learning support (aOR,3.2:95%CI, 1.3-7.2), ability to self-enroll to the platform (aOR5.4:95%CI, 3.1-9.4), ODeL training and orientation (aOR,2.7: 95%CI, 1.5-4.8) and ownership of a computer/ smartphone (aOR 7.4: 95% CI, 2.2-25.2). Successful maneuvering can be bolstered through access to e-learning tools, such as computers and smartphones, ICT support, and adequate ODeL training and orientation for students to the e-learning platform.
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References
- Abdulla, D. R., & Elmansoury, M. (2021). Online problem-based learning (pbl) during coronavirus pandemic: trial at the Libyan International Medical University.
- Al-Adwan, A. S., Albelbisi, N. A., Hujran, O., Al-Rahmi, W. M., & Alkhalifah, A. (2021). Developing a holistic success model for sustainable e-learning: A structural equation modeling approach. Sustainability, 13(16), 9453. https://doi.org/10.3390/su13169453
- Alsoufi., A, Alsuyihili., A, Misherghi., A, Elhadi., A (2020). Impact of the COVID-19 pandemic on medical education: Medical students’ knowledge, attitudes, and practices regarding electronic learning. PLOS ONE.https://doi.org/10.1371/journal.pone.0242905
- Alnagar, D. K. F. (2020). Using artificial neural networks to predict student satisfaction in e-learning. Am J Appl Math Stat, 8(3), 90-5.
- Al-Nefaie, S. (2015). Investigating factors influencing students’ attitude and performance when using web-enhanced learning in developing countries: The case of Saudi Arabia(Doctoral dissertation, Brunel University London). http://bura.brunel.ac.uk/handle/2438/12163
- Bashir, K. (2019). Modeling E-Learning Interactivity, Learner Satisfaction and Continuance Learning Intention in Ugandan Higher Learning Institutions. International Journal of Education and Development Using Information and Communication Technology, 15(1), n1.
- Bekele, T. A. (2010). Motivation and satisfaction in internet-supported learning environments: A review. Journal of Educational Technology & Society, 13(2), 116–127.
- Bolliger, D. U., & Halupa, C. (2012). Student perceptions of satisfaction and anxiety in an online doctoral program. Distance Education, 33(1), 81–98.
- Davis, F. D. (1989). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation, Massachusetts Institute of Technology).
- Gray K. & Tobin J. (2010). Introducing an online community into a clinical education setting: a pilot study of student and staff engagement and outcomes using blended learning. BMC Medical Education 10(1):6
- Hung, M.-L., Chou, C., Chen, C.-H., & Own, Z.-Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3), 1080–1090.
- Hurtado, S. et al. (2011) ‘“We do science here”: Underrepresented students’ interactions with faculty in different college contexts’, Journal of Social Issues, 67(3), 553–579.
- Jiang, M., & Ting, E. (2000). A study of factors influencing students’ perceived learning in a web-based course environment. International Journal of Educational Telecommunications, 6(4), 317–338.
- Kaliisa, R., & Picard, M. (2017). A systematic review on mobile learning in higher education: The African perspective. TOJET: The Turkish Online Journal of Educational Technology, 16(1).
- Kaushik, M. K., & Agrawal, D. (2021). Influence of technology readiness in adoption of e-learning. International Journal of Educational Management, 35(2), 483-495.
- Leung W. C. (2002). Competency based medical training: review. British Medical Journal 325(7366):693–696.
- Mella-Norambuena, J., Cobo-Rendón, R., Lobos, K., Sáez-Delgado, F., & Maldonado-Trapp, A. (2021). Smartphone use among undergraduate STEM students during COVID-19: An opportunity for higher education?. Education Sciences, 11(8), 417.
- McCoy, L., Pettit, R., Lewis, J., Bennett, T., Carrasco, N., Brysacz, S., Makin, I., Hutman, R. & Schwartz, F. (2015). Developing Technology-Enhanced Active Learning for Medical Education: Challenges, Solutions, and Future Directions. Journal of Osteopathic Medicine, 115(4), 202-211. https://doi.org/10.7556/jaoa.2015.042
- Mohammadyari, S., & Singh, H. (2015). Understanding the effect of e-learning on individual performance: The role of digital literacy. Computers & Education, 82, 11-25.
- Nortvig, A. M., Petersen, A. K., & Balle, S. H. (2018). A literature review of the factors influencing e‑learning and blended learning in relation to learning outcome, student satisfaction and engagement. Electronic Journal of E-learning, 16(1), pp46-55.
- Regmi, K., & Jones, L. (2020). A systematic review of the factors–enablers and barriers–affecting e-learning in health sciences education. BMC medical education, 20(1), 1-18.
- Taylor, J. C. (2002). Teaching and learning online: The workers, the lurkers and the shirkers. Paper presented at the 2002 Conference on Research in Distance & Adult Learning in Asia.
- Twesigye., J (2020). COVID-19 Educational Disruption and Response: Rethinking e-Learning in Uganda. Konrad, Adenuer Stiftung. https://www.kas.de/documents/.
- Violante, M. G., & Vezzetti, E. (2015). Virtual interactive e‐learning application: An evaluation of the student satisfaction. Computer Applications in Engineering Education, 23(1), 72–91.
- Twesigye., J (2020). COVID-19 Educational Disruption and Response: Rethinking e-Learning in Uganda. Konrad, Adenuer Stiftung. https://www.kas.de/documents/.
- Violante, M. G., & Vezzetti, E. (2015). Virtual interactive e‐learning application: An evaluation of the student satisfaction. Computer Applications in Engineering Education, 23(1), 72–91.
References
Abdulla, D. R., & Elmansoury, M. (2021). Online problem-based learning (pbl) during coronavirus pandemic: trial at the Libyan International Medical University.
Al-Adwan, A. S., Albelbisi, N. A., Hujran, O., Al-Rahmi, W. M., & Alkhalifah, A. (2021). Developing a holistic success model for sustainable e-learning: A structural equation modeling approach. Sustainability, 13(16), 9453. https://doi.org/10.3390/su13169453
Alsoufi., A, Alsuyihili., A, Misherghi., A, Elhadi., A (2020). Impact of the COVID-19 pandemic on medical education: Medical students’ knowledge, attitudes, and practices regarding electronic learning. PLOS ONE.https://doi.org/10.1371/journal.pone.0242905
Alnagar, D. K. F. (2020). Using artificial neural networks to predict student satisfaction in e-learning. Am J Appl Math Stat, 8(3), 90-5.
Al-Nefaie, S. (2015). Investigating factors influencing students’ attitude and performance when using web-enhanced learning in developing countries: The case of Saudi Arabia(Doctoral dissertation, Brunel University London). http://bura.brunel.ac.uk/handle/2438/12163
Bashir, K. (2019). Modeling E-Learning Interactivity, Learner Satisfaction and Continuance Learning Intention in Ugandan Higher Learning Institutions. International Journal of Education and Development Using Information and Communication Technology, 15(1), n1.
Bekele, T. A. (2010). Motivation and satisfaction in internet-supported learning environments: A review. Journal of Educational Technology & Society, 13(2), 116–127.
Bolliger, D. U., & Halupa, C. (2012). Student perceptions of satisfaction and anxiety in an online doctoral program. Distance Education, 33(1), 81–98.
Davis, F. D. (1989). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation, Massachusetts Institute of Technology).
Gray K. & Tobin J. (2010). Introducing an online community into a clinical education setting: a pilot study of student and staff engagement and outcomes using blended learning. BMC Medical Education 10(1):6
Hung, M.-L., Chou, C., Chen, C.-H., & Own, Z.-Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3), 1080–1090.
Hurtado, S. et al. (2011) ‘“We do science here”: Underrepresented students’ interactions with faculty in different college contexts’, Journal of Social Issues, 67(3), 553–579.
Jiang, M., & Ting, E. (2000). A study of factors influencing students’ perceived learning in a web-based course environment. International Journal of Educational Telecommunications, 6(4), 317–338.
Kaliisa, R., & Picard, M. (2017). A systematic review on mobile learning in higher education: The African perspective. TOJET: The Turkish Online Journal of Educational Technology, 16(1).
Kaushik, M. K., & Agrawal, D. (2021). Influence of technology readiness in adoption of e-learning. International Journal of Educational Management, 35(2), 483-495.
Leung W. C. (2002). Competency based medical training: review. British Medical Journal 325(7366):693–696.
Mella-Norambuena, J., Cobo-Rendón, R., Lobos, K., Sáez-Delgado, F., & Maldonado-Trapp, A. (2021). Smartphone use among undergraduate STEM students during COVID-19: An opportunity for higher education?. Education Sciences, 11(8), 417.
McCoy, L., Pettit, R., Lewis, J., Bennett, T., Carrasco, N., Brysacz, S., Makin, I., Hutman, R. & Schwartz, F. (2015). Developing Technology-Enhanced Active Learning for Medical Education: Challenges, Solutions, and Future Directions. Journal of Osteopathic Medicine, 115(4), 202-211. https://doi.org/10.7556/jaoa.2015.042
Mohammadyari, S., & Singh, H. (2015). Understanding the effect of e-learning on individual performance: The role of digital literacy. Computers & Education, 82, 11-25.
Nortvig, A. M., Petersen, A. K., & Balle, S. H. (2018). A literature review of the factors influencing e‑learning and blended learning in relation to learning outcome, student satisfaction and engagement. Electronic Journal of E-learning, 16(1), pp46-55.
Regmi, K., & Jones, L. (2020). A systematic review of the factors–enablers and barriers–affecting e-learning in health sciences education. BMC medical education, 20(1), 1-18.
Taylor, J. C. (2002). Teaching and learning online: The workers, the lurkers and the shirkers. Paper presented at the 2002 Conference on Research in Distance & Adult Learning in Asia.
Twesigye., J (2020). COVID-19 Educational Disruption and Response: Rethinking e-Learning in Uganda. Konrad, Adenuer Stiftung. https://www.kas.de/documents/.
Violante, M. G., & Vezzetti, E. (2015). Virtual interactive e‐learning application: An evaluation of the student satisfaction. Computer Applications in Engineering Education, 23(1), 72–91.
Twesigye., J (2020). COVID-19 Educational Disruption and Response: Rethinking e-Learning in Uganda. Konrad, Adenuer Stiftung. https://www.kas.de/documents/.
Violante, M. G., & Vezzetti, E. (2015). Virtual interactive e‐learning application: An evaluation of the student satisfaction. Computer Applications in Engineering Education, 23(1), 72–91.