VR as a choice: what drives learners’ technology acceptance?

• Published in: International Journal of Educational Technology in Higher Education Vol. 19; no. 1; pp. 1 - 21
• Main Authors: Noble, Sean M., Saville, Jason D., Foster, Lori L.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 31.01.2022; BioMed Central, Ltd; Springer Nature B.V; SpringerOpen
• Subjects: Adoption (Ideas); College Students; Computer Appl. in Social and Behavioral Sciences; Computer Attitudes; Computer Science; Computer Simulation; Computers and Education; Educational Objectives; Educational psychology; Educational Technology; Expectation; Higher Education; Humanities; Information Systems Applications (incl.Internet); Intention; Law; Learning; Post-secondary education; Predictor Variables; Preferences; Psychological factors; Psychological Patterns; Relative weight analysis; Research Article; Social Influences; Statistics for Social Sciences; Student attitudes; Technology acceptance; Technology Acceptance Model; Technology Uses in Education; Technology utilization; Universities; University students; UTAUT; Video Technology; Virtual reality; Vocational Schools; Technology acceptance; Relative weight analysis; UTAUT; Virtual reality; Post-secondary education
• ISSN: 2365-9440; 2365-9440
• DOI: 10.1186/s41239-021-00310-w

Post-secondary institutions are investing in and utilizing virtual reality (VR) for many educational purposes, including as a discretionary learning tool. Institutions such as vocational schools, community colleges, and universities need to understand what psychological factors drive students’ acceptance of VR for learning in discretionary contexts. The Unified Theory of Acceptance and Use of Technology (UTAUT; Venkatesh et al. in MIS Quarterly 27:425–478, 2003) offers a theoretical framework for understanding students’ receptivity to VR for learning. Undergraduate university students ( N  = 300) read a description of VR and video training mediums, then indicated which they would choose to learn a novel task. Three psychological variables—performance expectancy, effort expectancy, and social influence—tended to be related to acceptance of VR, which was measured in two ways: (a) rated intentions to use VR and (b) preference for VR over a video-based alternative. Relative weight analyses compared the importance of the three predictors and revealed that performance expectancy tended to be the most influential antecedent of VR acceptance.