Meta-analysis of the Impact of Virtual Reality Assisted Teaching on Students’ Attitudes

Learning attitude is one of the important factors in evaluating the effectiveness of virtual reality technology-assisted teaching. However, existing empirical studies are controversial as to whether virtual reality technology promotes learning attitudes than traditional forms of education and lack of systematic review arguments. To clarify the impact of virtual reality on learning attitudes, based on a meta-analytic approach, this paper systematically analyzes 29 empirical research papers from internationally literature sources, exploring the moderating effects of regulating variables on the impact of virtual reality for learning attitudes in terms of the dimensions of discipline, academic level, duration and the type of virtual reality technology. The results show that virtual reality technology has only a moderate positive effect on learning attitudes (total effect value g = 0.666). The moderating variables reveal that there are significant differences for different disciplines in the effects of learning attitudes, while the effects for academic levels are consistent with the Gaussian distribution of the age; an optimal interval exists for the length of 1-6 weeks, while the moderating effect is basically absent for less than 1 week and greater than 6 weeks; there are differences in the effects of the type of virtual reality technology, with no significant moderating effect presenting. The study suggests that teaching based on virtual reality technology affecting learning attitudes should be improved in terms of content selection, object selection, and class time optimization, so as to effectively realize its efficacy in promoting learning attitudes.

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Published
2024-09-13
DOI
https://doi.org/10.1109/icet62460.2024.10868635
Primary Topic
Education and Learning Interventions
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article
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article

Meta-analysis of the Impact of Virtual Reality Assisted Teaching on Students’ Attitudes

Jing Liu, Jun Han, Chenxi Dang
Education and Learning Interventions
article

Meta-analysis of the Impact of Virtual Reality Assisted Teaching on Students’ Attitudes

Jing Liu, Jun Han, Chenxi Dang
article en

Abstract

Learning attitude is one of the important factors in evaluating the effectiveness of virtual reality technology-assisted teaching. However, existing empirical studies are controversial as to whether virtual reality technology promotes learning attitudes than traditional forms of education and lack of systematic review arguments. To clarify the impact of virtual reality on learning attitudes, based on a meta-analytic approach, this paper systematically analyzes 29 empirical research papers from internationally literature sources, exploring the moderating effects of regulating variables on the impact of virtual reality for learning attitudes in terms of the dimensions of discipline, academic level, duration and the type of virtual reality technology. The results show that virtual reality technology has only a moderate positive effect on learning attitudes (total effect value g = 0.666). The moderating variables reveal that there are significant differences for different disciplines in the effects of learning attitudes, while the effects for academic levels are consistent with the Gaussian distribution of the age; an optimal interval exists for the length of 1-6 weeks, while the moderating effect is basically absent for less than 1 week and greater than 6 weeks; there are differences in the effects of the type of virtual reality technology, with no significant moderating effect presenting. The study suggests that teaching based on virtual reality technology affecting learning attitudes should be improved in terms of content selection, object selection, and class time optimization, so as to effectively realize its efficacy in promoting learning attitudes.

Capital Normal University (CN)
Openalex Percentile: Top 57%
Education and Learning Interventions
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Meta-analysis of the Impact of Virtual Reality Assisted Teaching on Students’ Attitudes — Jing Liu, Jun Han, et al. · (2024) | TGRS Research Map | TGRS