Abstract
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.
Highlights
Colleges and universities across the globe strive to ensure the students enrolled have access and exposure to technologies that will help them learn and later transition to the world of work
The present study addresses this gap with an approach rarely, if ever, employed in the technology acceptance literature to date: Johnson’s (2000) relative weight analysis (RWA)
We examine as a research question whether performance expectancy, effort expectancy, and social influence differentially influence students’ acceptance of virtual reality (VR)
Summary
Colleges and universities across the globe strive to ensure the students enrolled have access and exposure to technologies that will help them learn and later transition to the world of work. While technology may be introduced in the classroom, often it is not. For example, a new piece of hardware or software in an on-campus makerspace studio. Students—including those with no experience with the technology—make the decision to use or to not use this resource. This raises interesting questions about what drives acceptance of a discretionary learning technology
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