Research Article

Comparative analysis of learning management systems usage among tertiary students in Ghana

Issah Bala Abdulai 1 * , Daniel Paa Korsah 2
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1 Kibi Presbyterian College of Education, Kibi, GHANA2 Komenda College of Education, Komenda, GHANA* Corresponding Author
Journal of Digital Educational Technology, 4(2), 2024, ep2414, https://doi.org/10.30935/jdet/14582
Published Online: 06 May 2024, Published: 01 July 2024
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ABSTRACT

The objective of this study was to employ the unified theory of acceptance and use of technology (UTAUT) model to compare the differences in learning management systems (LMSs) usage by age, gender, and institution type among tertiary students in Ghana. The research used a survey design to collect quantitative data for the study. Multi-stage sampling was used to sample 476 tertiary students from three categories of tertiary institutions: public universities, technical universities, and colleges of education. Questionnaires were employed as a means of data collection and the data were analyzed using ANOVA, independent sample t-test, and post-hoc analysis. The results indicate that there is a statistically significant difference in performance expectancy, effort expectancy, and behavioral intention between the groups of tertiary institution users of LMS. The study concluded that the usage and acceptance rate of LMS among tertiary students was moderate. This work is a valuable contribution to the existing body of knowledge. Thus, providing empirical data on the comparative analysis of LMS usage among Ghanaian tertiary students that has implication for policy and practice. The study recommends that tertiary institutions should develop policies governing the usage of LMS across their various campuses.

CITATION (APA)

Abdulai, I. B., & Korsah, D. P. (2024). Comparative analysis of learning management systems usage among tertiary students in Ghana. Journal of Digital Educational Technology, 4(2), ep2414. https://doi.org/10.30935/jdet/14582

REFERENCES

  1. Abbad, M. M. M. (2021). Using UTAUT model to understand students’ usage of e-learning systems in developing countries. Education and Information Technologies, 26, 7205-7224. https://doi.org/10.1007/s10639-021-10573-5
  2. Al-Gahtani, S. S. (2016). Empirical investigation of e-learning acceptance and assimilation: A structural equation model. Applied Computing and Informatics, 12(1), 27-50. https://doi.org/10.1016/j. aci.2014.09.001
  3. Alkharang, M. M. (2014). Factors that influence the adoption of e-learning: An empirical study in Kuwait [Doctoral Dissertation, Brunel University].
  4. Alshorman, B. A., & Bawaneh, A. K. (2018). Attitudes of faculty members and students towards the use of the LMS in teaching and learning. Turkish Online Journal of Educational Technology, 17(3), 1-15.
  5. Altawallbeh, M., Thiam, W., Alshourah, S., & Fong, S. F. (2015). Do the instructors differ in their behavioral intention to adopt e-learning based on age, gender, and internet experience? Journal of Education and Practice, 6, 41-51.
  6. Celikoz, N., & Erdogan, P. (2017). The investigation of preparatory school students’ attitudes towards learning management system. International Online Journal of Educational Sciences, 9, 243-261. https://doi.org/10.15345/iojes.2017.01.016
  7. Check, J., & Schutt, R. K. (2012). Survey research. In J. Check, & R. K. Schutt (Eds.), Research methods in education. SAGE. https://doi.org/10.4135/9781544307725.n8
  8. Chua, P. Y., Rezaei, S., Gu, M. L., Oh, Y., & Jambulingam, M. (2018). Elucidating social networking apps decisions: Performance expectancy, effort expectancy and social influence. Nankai Business Review International, 9(2), 118-142. https://doi.org/10.1108/NBRI-01-2017-0003
  9. Gyampoh, A. O., Ayitey, H. K., Fosu-Ayarkwah, C., Ntow, S. A., Akossah, J., Gavor, M., & Vlachopoulos, D. (2020). Tutor perception on personal and institutional preparedness for online teaching -learning during the COVID-19 crisis: The case of Ghanaian colleges of education. African Educational Research Journal, 8(3), 511-518. https://doi.org/10.30918/AERJ.83.20.088
  10. Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. (2017). An updated and expanded assessment of PLSSEM in information systems research. Industrial Management & Data Systems, 117(3), 442-458. https://doi.org/10.1108/IMDS-04-2016-0130
  11. Hwu, S. (2011). Concerns and professional development needs of university faculty in adopting online learning [PhD thesis, Kansas State University].
  12. Jambulingam, M. (2013). Behavioural intention to adopt mobile technology among tertiary students. World Applied Sciences Journal, 22(9), 1262-1271.
  13. Jamil, L. S. (2017). Assessing the behavioural intention of students towards learning management system, through technology acceptance model - Case of Iraqi universities. Journal of Theoretical and Applied Information Technology, 95(16), 3825-3840. http://www.jatit.org/volumes/Vol95No16/11Vol95No16.pdf
  14. Kamal, B. (2013). Concerns and professional development needs of faculty at King Abdul-Aziz University in Saudi Arabia in adopting online teaching [PhD thesis, Kansas State University].
  15. Kenya, N. (2007). Quality education in eastern and western sub-Saharan Africa. UNESCO-IBE.
  16. Kotoua, S., Ilkana, M., & Kilio, H. (2015). The growing of online education in sub-Saharan Africa: Case study Ghana. Social and Behavioural Sciences, 19(1), 2406-2411. https://doi.org/10.1016/j.sbspro.2015.04.670
  17. Li, Y., Wang, Q., & Campbell, J. (2015). Investigating gender and racial/ethnic invariance in use of a course management system in higher education. Education Sciences, 5, 179-198. https://doi.org/10.3390/educsci5020179
  18. Ozlem, E. K., & Ozhan, T. (2017). The acceptance and use of a virtual learning environment in higher education: An empirical study in Turkey, and the UK. International Journal of Educational Technology in Higher Education, 14(26), 2-15. https://doi.org/10.1186/s41239-017-0064-z
  19. Perera, R. H. A. T., & Abeysekera, N. (2022). Factors affecting learners’ perception of e-learning during the COVID-19 pandemic. Asian Association of Open Universities Journal, 17(1), 84-100. https://doi.org/10.1108/AAOUJ-10-2021-0124
  20. Piňosová, M. (2020). Questionnaire survey focused on the quality of the working environment of industrial plants: Case study. European Journal of Medical and Health Sciences, 2(6), 1-8. https://doi.org/10.24018/ejmed.2020.2.6.609
  21. Raman, A., Don, Y., Khalid, R., Hussin, F., Omar, M. S., & Ghani, M. (2014). Technology acceptance on smart board among teachers in terengganu using UTAUT model. Asian Social Science, 10(11), 84-91. https://doi.org/10.5539/ass.v10n11p84
  22. Ramírez-Correa, P. E., Arenas-Gaitán, J., & Rondán-Cataluña, F. J. (2015). Gender and acceptance of e-learning: A multi-group analysis based on a structural equation model among college students in Chile and Spain. PLoS ONE, 10(10), e0140460. https://doi.org/10.1371/journal.pone.0140460
  23. Swart, A. J. (2016). The effective use of a learning management system still promotes student engagement! In 2016 IEEE Global Engineering Education Conference (EDUCON) (pp. 40-44). IEEE. https://doi.org/10.1109/EDUCON.2016.7474528
  24. Tagoe, M. (2012). Students’ perceptions on incorporating e-learning into teaching and learning at the University of Ghana. International Journal of Education and Development Information and Communication and Technology, 8, 1-9.
  25. Tanye, H. A. (2017). Quality e-learning in distance learning: Benefits and implications for national e-learning policy in Ghana. International Journal of Multicultural and Multireligious Understandiding, 4(3), 1. https://doi.org/10.18415/ijmmu.v4i3.73
  26. Tarhini, A. (2013). The effects of individual-level culture and demographic characteristics on e-learning acceptance in Lebanon and England: A structural equation modelling approach. SSRN. https://doi.org/10.2139/ssrn.2725438
  27. Tarhini, A., Hone, K., & Liu, X. (2014a). Measuring the moderating effect of gender and age on e-learning acceptance in England: A structural equation modeling approach for an extended technology acceptance model. Journal of Educational Computing Research, 51(2), 163-184. https://doi.org/10.2190/EC.51.2.b
  28. Tarhini, A., Hone, K., & Liu, X. (2014b). The effects of individual differences on e-learning users’ behaviour in developing countries: A structural equation model. Computers in Human Behavior, 41(2014), 153-163. https://doi.org/10.1016/j.chb.2014.09.020
  29. Tarhini, A., Hone, K., Liu, X., & Tarhini, T. (2017). Examining the moderating effect of individual-level cultural values on users’ acceptance of e-learning in developing countries: A structural equation modeling of an extended technology acceptance model. Interactive Learning Environments, 25(3), 306-328. https://doi.org/10.1080/10494820.2015.1122635
  30. Tetteh, L. A., Krah, R., Ayamga, T. A., Ayarna-Gagakuma, L. A., Offei-Kwafo, K., & Gbade, V. A. (2023). COVID-19 pandemic and online accounting education: The experience of undergraduate accounting students in an emerging economy. Journal of Accounting in Emerging Economies, 13(14), 825-846. https://doi.org/10.1108/JAEE-07-2021-0242
  31. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
  32. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27, 425-478. https://doi.org/10.2307/30036540
  33. Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412
  34. Wang, J., Doll, W. J., Deng, X., Park, K., & Yang, M. (2013). The impact of faculty perceived reconfigurability of learning management systems on effective practices. Computers and Education, 61(1), 146-157. https://doi.org/10.1016/j.compedu.2012.09.005
  35. Weilage, C., & Stumpfegger, E. (2022). Technology acceptance by university lecturers: A reflection on the future of online and hybrid teaching. On the Horizon, 30(2), 112-121. https://doi.org/10.1108/OTH-09-2021-0110
  36. Wut, T. M., Lee, S. W., & Xu, J. (2022). How do facilitating conditions influence student-to-student interaction within an online learning platform? A new typology of the serial mediation model. Education Sciences, 12(5), 337. https://doi.org/10.3390/educsci12050337
  37. Yalman, M., Basaran, B., & Gonen, S. (2016). Attitudes of students taking distance education in theology undergraduate education program towards e-learning management system. Universal Journal of Educational Research, 4, 1708-1717. https://doi.org/10.13189/ujer.2016.040724
  38. Yeboah, D., & Nyagorme, P. (2022). Students’ acceptance of WhatsApp as teaching and learning tool in distance higher education in sub-saharan Africa. Cogent Education, 9(1), 2077045. https://doi.org/10.1080/2331186X.2022.2077045
  39. Zanjani, N., Edwards, S., Nykvist, S., & Shlomo, G. (2017). The important elements of LMS design that affect user engagement with e-learning tools within LMSs in the higher education sector. Australasian Journal of Educational Technology, 33(1), 19-31. https://doi.org/10.14742/ajet.2938