Students’ Perception of Google Classroom and Microsoft Teams Using TAM-Based Constructs
Keywords:
Technology Acceptance Model, Google Classroom, Microsoft Teams, Learning Management Systems, Students’ PerceptionAbstract
Purpose: This study examined undergraduate students’ perceptions of Google Classroom and Microsoft Teams using five constructs of the Technology Acceptance Model (TAM): Perceived Usefulness (PU), Perceived Ease of Use (PEU), Perceived Enjoyment (PE), Task-Technology Fit (TTF), and Perceived Resources (PR). A total of 300 students enrolled in a Thai university participated, with each course section using one of the two platforms for at least three weeks prior to data collection. Research design, data and methodology: A quantitative, cross-sectional survey design was employed. Data were analyzed using descriptive statistics, reliability analysis, and independent samples t-tests to compare perceptions between the platforms. Results: Students reported generally positive perceptions toward both LMSs, with all means falling within the “agree” range. Although Microsoft Teams showed slightly higher descriptive ratings, independent samples t-tests indicated no statistically significant differences across all constructs. Independent samples t-tests indicated no statistically significant differences between platforms across all five constructs (p > .05). Conclusions: The findings suggest that both platforms are perceived as similarly useful, intuitive, enjoyable, and adequately supported for academic tasks. Institutional decisions regarding LMS adoption may therefore rely on practical considerations such as integration, cost, or technical support rather than differences in student perception. The findings highlight that LMS adoption decisions in Thai university may not hinge on platform choice alone but on institutional support, instructional practices, and contextual readiness.
References
Al-Rahmi, W. M., Alzahrani, A. I., Yahaya, N., Alalwan, N., & Kamin, Y. B. (2021). Digital communication: The impact of social media on learning behavior and performance. Education and Information Technologies, 26(1), 1181-1198.
https://doi.org/10.1007/s10639-020-10336-2
Altunoğlu, B. D. (2017). Student evaluation of a learning management system: A case study of Moodle. Journal of Education and Practice, 8(7), 59-65.
Berking, P., & Gallagher, S. (2016). Design considerations for e-learning systems. Performance Improvement, 55(5), 14-24.
https://doi.org/10.1002/pfi.21687
Dahlstrom, E., Brooks, D. C., & Bichsel, J. (2014). The current ecosystem of learning management systems in higher education. EDUCAUSE Center for Analysis and Research.
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
Dobre, I. (2015). Learning management systems for higher education. International Journal of Advanced Educational Technologies, 12(3), 45-52.
Emelyanova, N., & Voronina, E. (2014). Introducing a learning management system at a Russian university: Students’ and teachers’ perceptions. The International Review of Research in Open and Distance Learning, 15(1), 272-289.
Eom, S. B. (2014). The effects of student-instructor interaction on student satisfaction in online learning. Journal of Asynchronous Learning Networks, 18(3), 1-15.
Garrison, D. R., Anderson, T., & Archer, W. (1999). Critical inquiry in a text-based environment. The Internet and Higher Education, 2(2-3), 87-105.
Garrison, D. R., Anderson, T., & Archer, W. (2010). The first decade of the community of inquiry framework. The Internet and Higher Education, 13(1-2), 5-9.
Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213-236. https://doi.org/10.2307/249689
Iftakhar, S. (2016). Google Classroom: What works and how? Journal of Education and Social Sciences, 3(2), 12-18.
Kurata, Y., Ishii, Y., & Ito, M. (2018). Using LMS during campus closures. Journal of Information Systems Education, 29(4), 215-224.
Liaw, S. S., Huang, H. M., & Chen, G. D. (2007). Surveying instructor and learner attitudes toward e-learning. Computers & Education, 49(4), 1066-1080.
López, Á., Alonso, L., & Barriuso, I. (2021). Microsoft Teams as a digital learning ecosystem. Education and Information Technologies, 26(6), 7569-7586. https://doi.org/10.1007/s10639-021-10661-7
Mwalumbwe, I., & Mtebe, J. S. (2017). Using learning analytics to predict students' performance. International Journal of Education and Development using ICT, 13(3), 134-152.
Ngeze, L. V. (2016). Use of Google Classroom in teaching. International Journal of Education and Development using ICT, 12(2), 105-127.
Park, Y. (2009). An analysis of the Technology Acceptance Model in understanding university students’ behavioral intention to use e-learning. Educational Technology & Society, 12(3), 150-162.
Shee, D. Y., & Wang, Y. S. (2008). Multi-criteria evaluation of the web-based e-learning system. Computers & Education, 50(1), 1035-1053.
Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008). What drives successful e-learning? Computers & Education, 50(4), 1183-1202.
Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695-704. https://doi.org/10.2307/25148660
Wang, Y. S. (2003). Assessment of learner satisfaction with asynchronous e-learning systems. Information & Management, 41(1), 75-86.
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