Online learning acceptance in higher education

Do we know everything?




online learning, technology acceptance models, higher education


Research on the acceptance of educational technologies in higher education has become a high priority in recent years, particularly in the context of COVID-19. Numerous articles have been published on the subject, building on basic technology adoption models to investigate the impact of a wide range of factors on adoption. The proliferation of variables frequently makes it challenging to interpret results and may generate confusion. In order to synthetize and organize this knowledge, the authors collected 143 variables from 47 systematically selected studies. Based on the results of an in-depth analysis of the content and effects of each variable, they developed a framework that helps provide insights into state-of-the-art research on technology acceptance in higher education. The results of their study not only summarize what they know so far but also point to gaps where new findings in the field are expected.


Download data is not yet available.

Author Biographies

Ágnes Halász, Corvinus University Budapest

PhD student

Zsófia Kenesei, Corvinus University of Budapest



Abdullah, F., & Ward, R. (2016). Developing a general extended Technology Acceptance Model for e-learning (GETAMEL) by analysing commonly used external factors. Computers in Human Behavior, 56, 238-256.

Batra R. & Ahtola O.T. (1990). Measuring the hedonic and utilitarian sources of consumer attitudes. Marketing Letters, 2(2), 159–70.

Granić, A. & Marangunić, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572–2593.

Kaushik, M.K. & Verma, D. (2020). Determinants of digital learning acceptance behavior: A systematic review of applied theories and implications for higher education. Journal of Applied Research in Higher Education, 12(4), 659-672.

Keszey, T., & Zsukk, J. (2017). Az új technológiák fogyasztói elfogadása. A magyar és nemzetközi szakirodalom áttekintése és kritikai értékelése. Vezetéstudomány – Budapest Management Review, 48(10), 38-47.

Keszey, T. (2020). Behavioural intention to use autonomous vehicles: Systematic review and empirical extension. Transportation Research Part C: Emerging Technologies, 119, 102732.

Martin, F. & Bolliger, D.U. (2022). Developing an online learner satisfaction framework in higher education through a systematic review of research. International Journal of Educational Technology in Higher Education 19 (50), 1-21.

Martin, F., Sun, T., & Westine, C.D. (2020). A systematic review of research on online teaching and learning from 2009 to 2018. Computers & Education, 159, 104009.

Moher, D., Liberati, A., Tetzlaff, J., Altman, D.G., & PRISMA Group*. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of Internal Medicine, 151(4), 264-269.

Ryan, R.M. & Deci, E.L. (2009). Promoting self-determined school engagement: Motivation, learning, and well-being. In K.R. Wenzel & A. Wigfield (Eds), Handbook of Motivation at School (pp. 171–195). Routledge/Taylor & Francis Group.

Paul, J. & Criado, A.R. (2020). The art of writing literature review: What do we know and what do we need to know? International Business Review, 29(4), 101717.

Siegrist, M. (2021). Trust and risk perception: A critical review of the literature. Risk Analysis, 41(3), 480-490.

Singh, V. & Thurman, A. (2019). How many ways can we define online learning? A systematic literature review of definitions of online learning (1988-2018). American Journal of Distance Education, 33(4), 289–306.

Szabó, K., Juhász, T., & Kenderfi, M. (2022). Felsőoktatás a COVID-19 árnyékában: Hazai tapasztalatok oktatói oldalról. Vezetéstudomány – Budapest Management Review, 53(6), 2-12.




How to Cite

Halász, Ágnes, & Kenesei, Z. (2024). Online learning acceptance in higher education: Do we know everything?. Vezetéstudomány Budapest Management Review, 55(5), 2–19.