Adoption and utilization of Moodle learning management system for emergency remote teaching: A UTAUT perspective

Educational Point, 1(2), 2024, e111
Publication date: Dec 19, 2024

ABSTRACT

This study evaluates the adoption of Moodle learning management system (LMS) for emergency remote teaching during the COVID-19 era by colleges of education (CoE) teachers in Ghana. The research highlights the level of experience of CoE teachers in their use of e-learning applications as well as the factors that influence their acceptance of Moodle LMS within the Unified Theory of Acceptance and Use of Technology framework. Three research questions guided the study: 1. What is the level of experience of CoE teachers in the use of e-learning applications? 2. What is the influence of performance expectancy, effort expectancy, and social influence of teachers on their behavioral intention to use Moodle LMS? 3. What is the influence of Facilitating Conditions, Service Quality, and Behavioral Intentions on teachers’ Use Behavior of Moodle LMS? The study used a descriptive cross-sectional survey approach to assess the experiences of CoE teachers in their use of e-learning applications as well as their behavioral intentions, and actual usage behaviors concerning Moodle. The quantitative approach was used to collect and analyze data. The findings reveal that social influence played the most crucial role in shaping educators’ behavioral intentions towards using Moodle, while performance expectancy and effort expectancy have a lesser impact. The study highlights the need to prioritize the service quality of learning management systems in CoEs. This can include routine system updates, intuitive user interfaces, and effective technical support to provide a smooth experience for educators. Recommendations are provided to enhance the adoption and utilization of Moodle, emphasizing the need for targeted professional development and improved infrastructural support. Implications of the results for understanding Moodle LMS adoption in emergency remote teaching contexts are discussed.

KEYWORDS

Moodle LMS e-learning emergency remote teaching UTAUT model colleges of education educators

CITATION (APA)

Korsah, D. P. (2024). Adoption and utilization of Moodle learning management system for emergency remote teaching: A UTAUT perspective. Educational Point, 1(2), e111.
Harvard
Korsah, D. P. (2024). Adoption and utilization of Moodle learning management system for emergency remote teaching: A UTAUT perspective. Educational Point, 1(2), e111.
Vancouver
Korsah DP. Adoption and utilization of Moodle learning management system for emergency remote teaching: A UTAUT perspective. Educational Point. 2024;1(2):e111.
AMA
Korsah DP. Adoption and utilization of Moodle learning management system for emergency remote teaching: A UTAUT perspective. Educational Point. 2024;1(2), e111.
Chicago
Korsah, Daniel Paa. "Adoption and utilization of Moodle learning management system for emergency remote teaching: A UTAUT perspective". Educational Point 2024 1 no. 2 (2024): e111.
MLA
Korsah, Daniel Paa "Adoption and utilization of Moodle learning management system for emergency remote teaching: A UTAUT perspective". Educational Point, vol. 1, no. 2, 2024, e111.

REFERENCES

  1. Adedoyin, O. B., & Soykan, E. (2020). COVID-19 pandemic and online learning: The challenges and opportunities. Interactive Learning Environments, 31(2), 863–875. https://doi.org/10.1080/10494820.2020.1813180
  2. Al-Emran, M., Elsherif, H. M., & Shaalan, K. (2016). Investigating attitudes towards the use of mobile learning in higher education. Computers in Human Behavior, 56, 93–102. https://doi.org/10.1016/j.chb.2015.11.033
  3. Amarh, G. A. (2022). Assessing the impact of COVID-19 on teaching and research: A Ghanaian perspective. International Journal of Constitutional Law, 20(3), 1342–1348. https://doi.org/10.1093/icon/moac065
  4. Beroíza-Valenzuela, F., & Salas-Guzmán, N. (2024). STEM and gender gap: A systematic review in WoS, Scopus, and ERIC databases (2012–2022). Frontiers in Education, 9, Article 1378640. https://doi.org/10.3389/feduc.2024.1378640
  5. Bervell, B., & Arkorful, V. (2020). LMS-enabled blended learning utilization in distance tertiary education: Establishing the relationships among facilitating conditions, voluntariness of use and use behaviour. International Journal of Educational Technology in Higher Education, 17, Article 6. https://doi.org/10.1186/s41239-020-0183-9
  6. Bervell, B., & Umar, I. N. (2017). A decade of LMS acceptance and adoption research in Sub-Sahara African higher education: A systematic review of models, methodologies, milestones and main challenges. Eurasia Journal of Mathematics, Science and Technology Education, 13(11), 7269–7286. https://doi.org/10.12973/ejmste/79444
  7. Cavus, N., Mohammed, Y. B., & Yakubu, M. N. (2021). Determinants of learning management systems during COVID-19 pandemic for sustainable education. Sustainability, 13(9), Article 5189. https://doi.org/10.3390/su13095189
  8. Brasca, C., Krishnan, C., Marya, V., Owen, K., Sirois, J., & Ziade, S. (2022, June). How technology is shaping learning in higher education. https://www.mckinsey.com/industries/education/our-insights/how-technology-is-shaping-learning-in-higher-education
  9. Dampson, D. G. (2021). Determinants of learning management system adoption in an era of COVID-19: Evidence from a Ghanaian university. European Journal of Education and Pedagogy, 2(3), 80–87. https://doi.org/10.24018/ejedu.2021. 2.3.94
  10. 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
  11. Dewi, E. A. S., Sanofi, Z., Pratamawaty, B. B., & Arifin, H. S. (2023). Implementation of the unified theory of acceptance and use of technology (UTAUT) model during the pandemic era: A systematic literature review (SLR). Malaysian Journal of Communication, 39(3), 313–350. https://doi.org/10.17576/JKMJC-2023-3903-17
  12. Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5–22. https://doi.org/10.1177/0047239520934018
  13. Gamage, S. H. P. W., Ayres, J. R., & Behrend, M. B. (2022). A systematic review on trends in using Moodle for teaching and learning. International Journal of STEM Education, 9, Article 9. https://doi.org/10.1186/s40594-021-00323-x
  14. Guetz, B., & Bidmon, S. (2022). The impact of social influence on the intention to use physician rating websites: Moderated mediation analysis using a mixed methods approach. Journal of Medical Internet Research, 24(11), Article e37505. https://doi.org/10.2196/37505
  15. Hu, J., Jiang, P., Zhou, Q., McKeand, A., & Choi, S.-K. (2020). Model validation methods for multiple correlated responses via covariance-overlap based distance. Journal of Mechanical Design, 142(4), Article 041401. https://doi.org/ 10.1115/1.4044330
  16. Husain, B., Idi, Y. N., & Basri, M. (2021). Teachers’ perceptions on adopting e-learning during COVID-19 outbreaks; advantages, disadvantages, suggestions. Jurnal Tarbiyah, 27(2), 41–57. https://doi.org/10.30829/tar.v27i2.738
  17. Khatimah, H., Susanto, P., & Abdullah, N. L. (2019). Hedonic motivation and social influence on behavioral intention of e-money: The role of payment habit as a mediator. International Journal of Entrepreneurship, 23(1). https://www.abacademies.org/articles/hedonic-motivation-and-social-influence-on-behavioral-intention-of-emoney-the-role-of-payment-habit-as-a-mediator-8006.html
  18. Korlat, S., Kollmayer, M., Holzer, J., Lüftenegger, M., Pelikan, E. R., Schober, B., & Spiel, C. (2021). Gender differences in digital learning during COVID-19: Competence beliefs, intrinsic value, learning engagement, and perceived teacher support. Frontiers in Psychology, 12, Article 637776. https://doi.org/10.3389/fpsyg.2021.637776
  19. Lai, Y.-H. (2017). The social influence on the behavioral intention to use mobile electronic medical records. In D. Król, N. T. Nguyen, & K. Shirai (Eds.), Advanced topics in intelligent information and database systems (pp. 141–150). Springer. https://doi.org/10.1007/978-3-319-56660-3_13
  20. Lavidas, K., Papadakis, S., Filippidi, A., Karachristos, C., Misirli, A., Tzavara, A., Komis, V., & Karacapilidis, N. (2023). Predicting the behavioral intention of Greek university faculty members to use Moodle. Sustainability, 15(7), Article 6290. https://doi.org/10.3390/su15076290
  21. Liao, S.-H., Hu, D.-C., & Chou, H.-L. (2022). Consumer perceived service quality and purchase intention: Two moderated mediation models investigation. Sage Open, 12(4). https://doi.org/10.1177/21582440221139469
  22. Meng, W., Yu, L., Liu, C., Pan, N., Pang, X., & Zhu, Y. (2024). A systematic review of the effectiveness of online learning in higher education during the COVID-19 pandemic period. Frontiers in Education, 8, Article 1334153. https://doi.org/10.3389/feduc.2023.1334153
  23. Morrison, C. M. (2003). Interpret with caution: Multicollinearity in multiple regression of cognitive data. Perceptual and Motor Skills, 97(1), 80–82. https://doi.org/10.2466/pms.2003.97.1.80
  24. Mulik, S., Srivastava, M., & Yajnik, N. (2018). Extending UTAUT model to examine MOOC adoption. NMIMS Management Review, 36(2), 26–41. https://management-review.nmims.edu/wp-content/uploads/2018/august/extending-utaut-model-to-examine-mooc-adoption-shrikant-mulik-dr-manjari-srivastava-dr-nilay-yajnik.pdf
  25. National Accreditation Board. (2019). Tertiary Education Statistics: Annual Statistics Report 2019. Accra: National Accreditation Board. https://gtec.edu.gh/download/file/TEI%20Statistical%20Report%202019.pdf
  26. Pedro, N. S., & Kumar, S. (2020). Institutional support for online teaching in quality assurance frameworks. Online Learrning, 24(3), 50–66. https://doi.org/10.24059/olj.v24i3.2309
  27. Qazi, A., Hasan, N., Abayomi‑Alli, O., Hardaker, G., Scherer, R., Sarker, Y., Paul, S. K., & Maitama, J. Z. (2022). Gender differences in information and communication technology use & skills: A systematic review and meta-analysis. Education and Information Technologies, 27, 4225–4258. https://doi.org/10.1007/s10639-021-10775-x
  28. Quansah, R., & Essiam, C. (2021). The use of learning management system (LMS) Moodle in the midst of COVID-19 pandemic: Students’ perspective. Journal of Educational Technology and Online Learning, 4(3), 418–413. https://doi.org/10.31681/jetol.934730
  29. Salloum, S. A., Alhamad, A. Q. M., Al-Emran, M., Monem, A. A., & Shaalan, K. (2019). Exploring students’ acceptance of e-learning through the development of a comprehensive Technology Acceptance Model. IEEE Access, 7, 128445–128462. https://doi.org/10.1109/ACCESS.2019.2939467
  30. Shams, M. S., Niazi, M. M., Gul, H., Mei, T. S., & Khan, K. U. (2022). E-learning adoption in higher education institutions during the COVID-19 pandemic: A multigroup analysis. Frontiers in Education, 6, Article 783087. https://doi.org/10.3389/feduc.2021.783087
  31. Simkus, J. (2023, July 31). Cross-sectional study: Definition, designs & examples. Simply Psychology. https://www.simply psychology.org/what-is-a-cross-sectional-study.html
  32. Supriyanto, A., Wiyono, B. B., & Burhanuddin, B. (2021). Effects of service quality and customer satisfaction on loyalty of bank customers. Cogent Business & Management, 8(1), Article 1937847. https://doi.org/10.1080/23311975. 2021.1937847
  33. Tondeur, J., van Braak, J., Ertmer, P. A., & Ottenbreit-Leftwich, A. (2017). Understanding the relationship between teachers’ pedagogical beliefs and technology use in education: A systematic review of qualitative evidence. Educational Technology Research and Development, 65(3), 555–575. https://doi.org/10.1007/s11423-016-9481-2
  34. UNESCO. (2020). Education: From COVID-19 school closures to recovery. UNESCO. https://en.unesco.org/covid19/ educationresponse
  35. United Nations. (2020). COVID-19: Socio-economic impact in Ghana. Accra: UNESCO, UNICEF, Ghana. Retrieved November 30, 2024, from https://ghana.un.org/sites/default/files/2020-05/No3_%20UN%20Ghana%20COVID-19%20Briefing%20Note_2020_05_11_FINAL%20v2.pdf
  36. 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
  37. Wichadee, S. (2018). Significant predictors for effectiveness of blended learning in a language course. JALT CALL Journal, 14(1), 25–42. https://doi.org/10.29140/jaltcall.v14n1.222
  38. Wu, S. (2020). Multicollinearity in Regression. Why it is a problem? How to check and fix it. Retrieved February 21, 2022, from https://towardsdatascience.com/multi-collinearity-in-regression-fe7a2c1467ea

LICENSE

Creative Commons License
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.