Using virtual reality for dynamic learning: an extended technology acceptance model

Abstract

Virtual reality (VR) is being researched and incorporated into curricula and training programs to expand educational opportunities and enhance learning across many fields. Although researchers are exploring the learning affordances associated with VR, research surrounding students’ perceptions of the technology, and intentions to use it for training has been neglected. The goal of this research was to determine the factors that influence students’ intention to use VR in a dynamic learning environment. An extended Technology Acceptance Model (TAM) was developed that incorporates factors related to education and the use of VR technology in training environments. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) processes were employed. Nine of 14 hypotheses in the original model were supported, and eight of the nine predictor factors of the model were determined to directly or indirectly impact behavioral intention (BI). The original TAM factors had the strongest relationships. Relationships between factors particularly relevant to VR technology and learning were also supported. The results of this study may guide other educators interested in incorporating VR into a dynamic learning environment.