Exploring structural relations among computer self-efficacy, perceived immersion, and intention to use virtual reality training systems

Abstract
The use of virtual reality (VR) training systems for education has grown in popularity in recent years. Scholars have reported that self-efficacy and interactivity are important predictors of learning outcomes in virtual learning environments, but little empirical research has been conducted to explain how computer self-efficacy (as a subcategory of self-efficacy) and perceived immersion (as a correlate of interactivity) are connected to the intention to use VR training systems. The present study aims to determine which factors significantly influence behavioral intention when students are exposed to VR training systems via an updated technology acceptance frame by incorporating the constructs of computer self-efficacy and perceived immersion simultaneously. We developed a VR training system regarding circuit connection and a reliable and validated instrument including 9 subscales. The sample data were collected from 124 junior middle school students and 210 senior high school students in two schools located in western China. The samples were further processed into a structural equation model with path analysis and cohort analysis. The results showed that the intention to use VR training systems was indirectly influenced by computer self-efficacy but directly influenced by perceived immersion (β = 0.451). However, perceived immersion seemed to be influenced mostly by learner interaction (β = 0.332). Among external variables, learner interaction (β = 0.149) had the largest total effect on use intention, followed by facilitating conditions (β = 0.138), computer self-efficacy (β = 0.104), experimental fidelity (β = 0.083), and subjective norms (β = 0.077). The moderating roles of gender differences, grade level, and previous experience in structural relations were also identified. The findings of the present study highlight the ways in which factors and associations are considered in the practical development of VR training systems.
Funding Information
  • Social Science Planning Foundation of Chongqing (2018BS100)
  • Fundamental Research Funds for the Central Universities (SWU2109320)