University students’ acceptance of video-conferencing for learning of mathematics in the post-COVID-19 era

Mailizar Mailizar; Ega Gradini; Tommy Tanu Wijaya; Abdulsalam Al-Manthari

doi:10.30935/cedtech/16824

Mailizar Mailizar ¹ ^* , Ega Gradini ², Tommy Tanu Wijaya ³, Abdulsalam Al-Manthari ⁴

More Detail

CONT ED TECHNOLOGY, Volume 17, Issue 4, Article No: ep590

https://doi.org/10.30935/cedtech/16824

Submitted: 30 March 2023, Published Online: 28 August 2025

OPEN ACCESS 89 Views 23 Downloads

Download Full Text (PDF)

Abstract

This study aims to examine the factors that influence university students’ behavioral intention in accepting video-conferencing for learning mathematics in the post-COVID-19 era. Video-conferencing as a learning tool has been widely used to establish effective communication among learners, teachers, and peers. This is particularly valuable in situations where face-to-face communication is not possible, such as during the COVID-19 pandemic. As the pandemic comes to an end, it is unclear whether video-conferencing will continue to be widely used as a teaching and learning tool. This study extends the technology acceptance model (TAM) by adding digital literacy (critical use, technology focused, and digital reading) and social presence (SC) as external factors. Extended TAM with digital literacy and SC as factors provide understanding on how university students’ digital literacy level and their connection and engagement with others influences their acceptance of video-conferencing for learning. The participants include 238 students from six universities in Indonesia (three public universities and three private universities), who enrolled in bachelor’s degree of mathematics and mathematics education. The questionnaire consisted of 40 items administered online to students selected by random sampling. A partial least square-structural equation modelling approach was used to analyze the measurement model, test the path, and draw conclusions. The findings of this study shows that attitude is the most important factor that has influenced the intention to employ video-conferencing after a pandemic situation. In addition, SC is considered the most significant factor in students’ attitudes towards the use of video-conferencing in the post-COVID-19 era.

Keywords: TAM, video conferencing acceptance, post-COVID-19, university student

References

Alelaiwi, A., Alghamdi, A., Shorfuzzaman, M., Rawashdeh, M., Hossain, M. S., & Muhammad, G. (2015). Enhanced engineering education using smart class environment. Computers in Human Behavior, 51, 852–856. https://doi.org/10.1016/j.chb.2014.11.061
Alfadda, H. A., & Mahdi, H. S. (2021). Measuring students’ use of Zoom application in language course based on the technology acceptance model (TAM). Journal of Psycholinguistic Research, 50(4), 883–900. https://doi.org/10.1007/s10936-020-09752-1
Beriswill, J. (2018). Zoom redefines web conferencing for education. In Proceedings of the E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 1208–1211). https://www.learntechlib.org/primary/p/185333/
Biocca, F., & Harms, C. (2002). Defining and measuring social presence: Contribution to the networked minds theory and measure. In Proceedings of PRESENCE (pp. 7–36).
Biocca, F., Harms, C., & Burgoon, J. K. (2003). Toward a more robust theory and measure of social presence: Review and suggested criteria. Presence: Teleoperators and Virtual Environments, 12(5), 456–480. https://doi.org/10.1162/105474603322761270
Bond, M. (2021). Schools and emergency remote education during the COVID-19 pandemic: A living rapid systematic review. Asian Journal of Distance Education, 15(2), 191–247. https://doi.org/10.5281/zenodo.4425683
Bonk, C. J. (2020). Pandemic ponderings, 30 years to today: Synchronous signals, saviors, or survivors? Distance Education, 41(4), 589–599. https://doi.org/10.1080/01587919.2020.1821610
Chen, J., Chow, A., Fadavi, D., Long, C., Sun, A. H., Cooney, C. M., & Broderick, K. P. (2021a). The Zoom boom: How video calling impacts attitudes towards aesthetic surgery in the COVID-19 era. Aesthetic Surgery Journal, 41(12), NP2086–NP2093. https://doi.org/10.1093/asj/sjab274
Chen, J., Lin, C.-H., & Chen, G. (2021b). A cross-cultural perspective on the relationships among social media use, self-regulated learning and adolescents’ digital reading literacy. Computers & Education, 175, Article 104322. https://doi.org/10.1016/j.compedu.2021.104322
Cigdem, H., & Topcu, A. (2015). Predictors of instructors’ behavioral intention to use learning management system: A Turkish vocational college example. Computers in Human Behavior, 52, 22–28. https://doi.org/10.1016/j.chb.2015.05.049
Creswell, J. W. (2012). Educational research: Planning, conducting and evaluating quantitative and qualitative research (4th ed.). Pearson.
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results [PhD thesis, Massachusetts Institute of Technology].
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
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
Donkor, F. (2010). The comparative instructional effectiveness of print-based and video-based instructional materials for teaching practical skills at a distance. International Review of Research in Open and Distributed Learning, 11(1), 96–116. https://doi.org/10.19173/irrodl.v11i1.792
Estriegana, R., Medina-Merodio, J.-A., & Barchino, R. (2019). Student acceptance of virtual laboratory and practical work: An extension of the technology acceptance model. Computers & Education, 135, 1–14. https://doi.org/10.1016/j.compedu.2019.02.010
Fathema, N., Shannon, D., & Ross, M. (2015). Expanding the technology acceptance model (TAM) to examine faculty use of learning management systems (LMSs) in higher education institutions. Journal of Online Learning & Teaching, 11(2), 210–232.
Galanti, T. M. L., Baker, C. K., Morrow-Leong, K., & Kraft, T. (2021). Enriching TPACK in mathematics education: using digital interactive notebooks in synchronous online learning environments. Interactive Technology and Smart Education, 18(3), 345–361. https://doi.org/10.1108/ITSE-08-2020-0175
Hair, J., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). SAGE.
Hargittai, E., Gruber, J., Djukaric, T., Fuchs, J., & Brombach, L. (2020). Black box measures? How to study people’s algorithm skills. Information, Communication & Society, 23(5), 764–775. https://doi.org/10.1080/1369118x.2020.1713846
Harman, C., & Dorman, M. (1998). Enriching distance teaching and learning of undergraduate mathematics using videoconferencing and audiographics. Distance Education, 19(2), 299–318. https://doi.org/10.1080/0158791980190208
Helsper, E. J. (2021). The digital disconnect: The social causes and consequences of digital inequalities. SAGE. https://doi.org/10.4135/9781526492982
Hennessy, S., D’Angelo, S., McIntyre, N., Koomar, S., Kreimeia, A., Cao, L., Brugha, M., & Zubairi, A. (2022). Technology use for teacher professional development in low-and middle-income countries: A systematic review. Computers and Education Open, 3, Article 100080. https://doi.org/10.1016/j.caeo.2022.100080
Hersh, S. (2020). Yes, your Zoom teaching can be first-rate. Inside Higher Ed. https://www.insidehighered.com/advice/2020/07/08/faculty-member-and-former-ad-executive-offers-six-steps-improving-teaching-zoom
Hussein, Z. (2017). Leading to intention: The role of attitude in relation to technology acceptance model in e-learning. Procedia Computer Science, 105, 159–164. https://doi.org/10.1016/j.procs.2017.01.196
Kay, R., & Kletskin, I. (2012). Evaluating the use of problem-based video podcasts to teach mathematics in higher education. Computers and Education, 59(2), 619–627. https://doi.org/10.1016/j.compedu.2012.03.007
Kehrwald, B. (2008). Understanding social presence in text-based online learning environments. Distance Education, 29(1), 89–106. https://doi.org/10.1080/01587910802004860
Kimmons, R., & Hall, C. (2016). Emerging technology integration models. In G. Veletsianos (Ed.), Emergence and Innovation in Digital Learning: Foundations and Applications (pp. 51–54). Athabasca University Press. https://www.degruyter.com/document/doi/10.15215/aupress/9781771991490.006/pdf
Koivula, M. (2018). The impacts of asynchronous video reflection on social presence: A case study. In Proceedings of the E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 1119–1128). Las Vegas, NV, United States: Association for the Advancement of Computing in Education (AACE). https://www.learntechlib.org/primary/p/185073/
Lakhal, S., Khechine, H., & Pascot, D. (2013). Student behavioural intentions to use desktop video conferencing in a distance course: Integration of autonomy to the UTAUT model. Journal of Computing in Higher Education, 25(2), 93–121. https://doi.org/10.1007/s12528-013-9069-3
List, A., Brante, E. W., & Klee, H. L. (2020). A framework of pre-service teachers’ conceptions about digital literacy: Comparing the United States and Sweden. Computers and Education, 148, Article 103788. https://doi.org/10.1016/j.compedu.2019.103788
Lowenthal, P. R. (2010). Social presence. In S. Dasgupta (Ed.), Social computing (pp. 129–136). IGI Global. https://doi.org/10.4018/978-1-60566-984-7.ch011
Mailizar, M., Almanthari, A., & Maulina, S. (2021a). Examining teachers’ behavioral intention to use e-learning in teaching of mathematics: An extended TAM model. Contemporary Educational Technology, 13(2), Article ep298. https://doi.org/10.30935/cedtech/9709
Mailizar, M., Burg, D., & Maulina, S. (2021b). Examining university students’ behavioural intention to use e-learning during the COVID-19 pandemic: An extended TAM model. Education and Information Technologies, 26(6), 7057–7077. https://doi.org/10.1007/s10639-021-10557-5
Mailizar, M., Umam, K., & Elisa, E. (2022). The impact of digital literacy and social presence on teachers’ acceptance of online professional development. Contemporary Educational Technology, 14(4), Article ep384. https://doi.org/10.30935/cedtech/12329
Miyazaki, M., Fujita, T., Jones, K., & Iwanaga, Y. (2017). Designing a web-based learning support system for flow-chart proving in school geometry. Digital Experiences in Mathematics Education, 3(3), 233–256. https://doi.org/10.1007/s40751-017-0034-z
Mohammadyari, S., & Singh, H. (2015). Understanding the effect of e-learning on individual performance: The role of digital literacy. Computers & Education, 82, 11–25. https://doi.org/10.1016/j.compedu.2014.10.025
Myers, M. P., & Schiltz, P. M. (2012). Use of illuminate in online teaching of statistics in the health sciences. Journal of Research in Innovative Teaching, 5(1).
Ng, W. (2012). Can we teach digital natives digital literacy? Computers and Education, 59(3), 1065–1078. https://doi.org/10.1016/j.compedu.2012.04.016
OECD. (2015). Students, computers and learning: Making the connection. OECD Publishing. https://doi.org/10.1787/9789264239555-en
Pangrazio, L., & Selwyn, N. (2021). Towards a school-based ‘critical data education’. Pedagogy, Culture & Society, 29(3), 431–448. https://doi.org/10.1080/14681366.2020.1747527
Phelps, A., & Vlachopoulos, D. (2020). Successful transition to synchronous learning environments in distance education: A research on entry-level synchronous facilitator competencies. Education and Information Technologies, 25(3), 1511–1527. https://doi.org/10.1007/s10639-019-09989-x
Prior, D. D., Mazanov, J., Meacheam, D., Heaslip, G., & Hanson, J. (2016). Attitude, digital literacy and self efficacy: Flow-on effects for online learning behavior. The Internet and Higher Education, 29, 91–97. https://doi.org/10.1016/j.iheduc.2016.01.001
Reiber-Kuijpers, M., Kral, M., & Meijer, P. (2021). Digital reading in a second or foreign language: A systematic literature review. Computers & Education, 163, Article 104115. https://doi.org/10.1016/j.compedu.2020.104115
Robinson, L., Schulz, J., Blank, G., Ragnedda, M., Ono, H., Hogan, B., Mesch, G. S., Cotton, S. R., Kretchmer, S. B., Hale, T. M., Drabowicz, T., Yan, P., Wellman, B., Harper, M.-G., Quan-Haase, A., Dunn, H. S., Casili, A. A., Tubaro, P., Carvath, R., ..., & Khilnani, A. (2020). Digital inequalities 2.0: Legacy inequalities in the information age. First Monday, 25(7). https://doi.org/10.5210/fm.v25i7.10842
Saadé, R., & Bahli, B. (2004). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: An extension of the technology acceptance model. Information and Management, 42(2), 317–327. https://doi.org/10.1016/j.im.2003.12.013
Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009
Shih, H.-P. (2004). Extended technology acceptance model of Internet utilization behavior. Information & Management, 41(6), 719–729. https://doi.org/10.1016/j.im.2003.08.009
Smith, J. A., & Sivo, S. A. (2012). Predicting continued use of online teacher professional development and the influence of social presence and sociability. British Journal of Educational Technology, 43(6), 871–882. https://doi.org/10.1111/j.1467-8535.2011.01223.x
Starr-Glass, D. (2020). Encouraging engagement: Video-conference augmentation of online distance learning environments. On the Horizon, 28(3), 125–132. https://doi.org/10.1108/OTH-06-2020-0020
Taylor, J. C., & Hwang, J. (2021). Science, technology, engineering, arts, and mathematics remote instruction for students with disabilities. Intervention in School and Clinic, 57(2), 111–118. https://doi.org/10.1177/10534512211001858
Teo, T., Milutinović, V., Zhou, M., & Banković, D. (2017). Traditional vs. innovative uses of computers among mathematics pre-service teachers in Serbia. Interactive Learning Environments, 25(7), 811–827. https://doi.org/10.1080/10494820.2016.1189943
Thompson, P. (2013). The digital natives as learners: Technology use patterns and approaches to learning. Computers & Education, 65, 12–33. https://doi.org/10.1016/j.compedu.2012.12.022
Tu, C.-H. (2000). On-line learning migration: From social learning theory to social presence theory in a CMC environment. Journal of Network and Computer Applications, 23(1), 27–37. https://doi.org/10.1006/jnca.1999.0099
Tu, C.-H., & McIsaac, M. (2002). The relationship of social presence and interaction in online classes. American Journal of Distance Education, 16(3), 131–150. https://doi.org/10.1207/S15389286AJDE1603_2
Turner, M., Kitchenham, B., Brereton, P., Charters, S., & Budgen, D. (2010). Does the technology acceptance model predict actual use? A systematic literature review. Information and Software Technology, 52(5), 463–479. https://doi.org/10.1016/j.infsof.2009.11.005
van Laar, E., van Deursen, A. J. A. M., van Dijk, J. A. G. M., & de Haan, J. (2020). Determinants of 21st-century skills and 21st-century digital skills for workers: A systematic literature review. Sage Open, 10(1). https://doi.org/10.1177/2158244019900176
Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451–481. https://doi.org/10.1111/j.1540-5915.1996.tb00860.x
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
Wells, J., Barry, R. M., & Spence, A. (2012). Using video tutorials as a carrot-and-stick approach to learning. IEEE Transactions on Education, 55(4), 453–458. https://doi.org/10.1109/TE.2012.2187451

Citation

Mailizar, M., Gradini, E., Wijaya, T. T., & Al-Manthari, A. (2025). University students’ acceptance of video-conferencing for learning of mathematics in the post-COVID-19 era. Contemporary Educational Technology, 17(4), ep590. https://doi.org/10.30935/cedtech/16824

Mailizar, M., Gradini, E., Wijaya, T. T., and Al-Manthari, A. (2025). University students’ acceptance of video-conferencing for learning of mathematics in the post-COVID-19 era. Contemporary Educational Technology, 17(4), ep590. https://doi.org/10.30935/cedtech/16824

Mailizar M, Gradini E, Wijaya TT, Al-Manthari A. University students’ acceptance of video-conferencing for learning of mathematics in the post-COVID-19 era. CONT ED TECHNOLOGY. 2025;17(4), ep590. https://doi.org/10.30935/cedtech/16824

Mailizar, Mailizar, Ega Gradini, Tommy Tanu Wijaya, and Abdulsalam Al-Manthari. "University students’ acceptance of video-conferencing for learning of mathematics in the post-COVID-19 era". Contemporary Educational Technology 2025 17 no. 4 (2025): ep590. https://doi.org/10.30935/cedtech/16824

Mailizar, Mailizar et al. "University students’ acceptance of video-conferencing for learning of mathematics in the post-COVID-19 era". Contemporary Educational Technology, vol. 17, no. 4, 2025, ep590. https://doi.org/10.30935/cedtech/16824

Mailizar M, Gradini E, Wijaya TT, Al-Manthari A. University students’ acceptance of video-conferencing for learning of mathematics in the post-COVID-19 era. CONT ED TECHNOLOGY. 2025;17(4):ep590. https://doi.org/10.30935/cedtech/16824