Elsevier

Computers & Education

Volume 134, June 2019, Pages 15-30
Computers & Education

Investigating the process of learning with desktop virtual reality: A structural equation modeling approach

https://doi.org/10.1016/j.compedu.2019.02.002Get rights and content

Highlights

  • Desktop VR features affect objective learning measures.

  • As part of an affective path, presence is a key variable affecting learning with VR.

  • As part of a cognitive path, cognitive benefits is central to learning with VR.

  • Efficacious VR features and high-level usability benefit learning outcomes.

Abstract

Virtual reality (VR) is gaining attention for having the potential to enrich students’ educational experiences. However, few studies have investigated the process of learning with VR. With the use of structural equation modeling, this study investigated the affective and cognitive factors that play a role in learning with a desktop VR simulation when pre-to post-test changes in motivation, self-efficacy, and knowledge about genetics are used as outcomes. The sample consisted of 199 university students (120 females), who learned from a desktop VR genetics simulation as a mandatory part of an undergraduate medical genetics course. The results indicated that there were two general paths by which desktop VR led to increases in the amount of learning following a VR lesson: an affective path that went through VR features, presence, intrinsic motivation, and self-efficacy; and a cognitive path that went through VR features, usability, cognitive benefits, and self-efficacy. It is concluded that learners may benefit from desktop VR simulations in which efficacious VR features and a high level of usability are emphasized.

Section snippets

Background

The education sector is currently experiencing an upsurge in the use of technologies such as virtual reality (VR) and interactive simulations for teaching and enriching students' educational experiences. According to Burbules (2006, p. 37) VR can be defined as “a computer-mediated simulation that is three-dimensional, multisensory, and interactive, so that the user's experience is “as if” inhabiting and acting within an external environment”. Depending on the system used, VR simulations may

Sample

The sample consisted of 199 (120 females and 79 males) first-year undergraduate students with a major in medicine from a large European University. The entire first year class of 300 students were contacted to participate in the study; however only those who gave permission to use the responses for research purposes were included in this study.

Procedures

The simulation session was a part of a mandatory medical genetics course that the students attended. The session lasted for three hours and was conducted

Results

A confirmatory factor analysis was conducted to test the fit of the hypothesized relationship between the constructs in the a priori model shown in Fig. 1. This hypothesized model nearly reached an acceptable fit (RMSEA = 0.063, CFI = 0.957, TLI = 0.952), but contained several non-significant paths which were deleted by an iterative procedure. Each of these paths were evaluated and removed one at a time based on the greatest misfit until all of the remaining paths were significant. This

Empirical contributions

The major empirical contribution of this paper is the finding that there are two paths that lead to learning with desktop VR when measures of pre-to post-test change are used as dependent variables. These are labeled the affective and the cognitive paths, and provide a framework by which learning in VR can be investigated.

Conclusions

Through the use of SEM, the present study tested a model based on previous work in the field of learning with VR. This resulted in a simplified model with two general paths by which the desktop VR simulation led to increased learning; an affective path in which presence was the key psychological variable; and a cognitive path with cognitive benefits as the key psychological variable. Furthermore, the influence of presence and cognitive benefits on the process of learning in VR was underscored

Acknowledgements

We would like to thank Anne Nørremølle, Ainara Lopez Cordoba, Julie Wulff, Jakob Wandall as well as all of the teachers at the Department of Cellular and Molecular Medicine at the University of Copenhagen who helped collect data for this study. We would also like to thank all of the employees at Labster who helped us develop and implement the Cytogenetics simulation in this study. This research was supported by Innovation Fund Denmark.

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