Behavior and self-efficacy modulate learning in virtual reality simulations for training: a structural equation modeling approach - Mousavi, S. M. Ali; Powell, Wendy; Louwerse, Max M.; Hendrickson, Andrew T. (Frontiers in Virtual Reality, 2023)
There is a rising interest in using virtual reality (VR) applications in learning, yet different studies have reported different findings for their impact and effectiveness. The current paper addresses this heterogeneity in the results. Moreover, contrary to most studies, we use a VR application actually used in industry thereby addressing ecological validity of the findings. In two studies, we explored the effects of an industrial VR safety training application on learning. In our first study, we examined both interactive VR and passive monitor viewing. Using univariate, comparative, and correlational analytical approaches, the study demonstrated a significant increase in self-efficacy and knowledge scores in interactive VR but showed no significant differences when compared to passive monitor viewing. Unlike passive monitor viewing, however, the VR condition showed a positive relation between learning gains and self-efficacy. In our subsequent study, a Structural Equation Model (SEM) demonstrated that self-efficacy and users' simulation performance predicted the learning gains in VR. We furthermore found that the VR hardware experience indirectly predicted learning gains through self-efficacy and user simulation performance factors. Conclusively, the findings of these studies suggest the central role of self-efficacy to explain learning gains generalizes from academic VR tasks to those in use in industry training. In addition, these results point to VR behavioral markers that are indicative of learning.