Job relevance or perceived usefulness? What features of immersive virtual reality software predict intention to use in a future project-based-learning scenario: a mixed method approach

Abstract

Not only since COVID-19, the topic of decentralized working and learning methods is becoming increasingly important for various reasons. New virtual reality technologies enable learning in immersive scenarios, which is good when learning from home is advised. However, not all immersive Virtual Reality (iVR) training incorporates learning systems that support complex, realistic, practical tasks that lead to a product or enable acquiring knowledge and life-enhancing skills like project-based learning. Although there are many iVR applications available that support project management, the specific features of these applications that lead to the intention to use (and therefore life-enhancing skills) have yet to be discovered. In this exploratory mixed-method study, we investigated the question of the importance of perceived usefulness (PU) and job relevance (JR) as predictors of intention to use (ItU) in a selection of immersive iVR application features. We started with market research and aggregated 88 software features in 13 categories of 34 professional iVR applications. After an expert selection and ranking procedure, a survey was developed. After deriving from the TAM 2 model and with a sample n = 103, we computed the relationship of JR, PU, and ItU. Although high values were generally observed, we found that the importance of PU is higher than JR when it comes to ItU. Limitations of the study are discussed, and suggestions for further research are given.