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Research Article

Can desktop virtual reality effectively enhance academic achievement? —A meta-analysis

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Published online: 16 May 2024
 

ABSTRACT

Virtual Reality (VR) is gradually integrating into classroom teaching, emerging as a new trend in educational development in the era of artificial intelligence. Desktop virtual reality stands out due to its lower cost and greater convenience. To elucidate the effectiveness of desktop virtual reality in learning, this paper employs a meta-analysis to systematically analyze 31 relevant studies. The findings suggest that desktop virtual reality can effectively enhance students’ academic achievement, fostering improvements in their knowledge, emotions, and abilities. Moreover, its effects in developing countries surpass those in developed countries. There is a linearly increasing relationship between the duration of the experiment and students’ academic achievement. Notably, there is no significant difference in learning outcomes across different subjects, with the implementation in high school showing the most promising results. The immersive VR teaching effectiveness in the control group slightly exceeds that of traditional teaching, particularly at higher levels.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the School of Shaanxi Normal University teacher development, Shaanxi Teachers Development Research Institute: [Project number 2023JSZ012]; Recipients: Wenlan Zhang.

Notes on contributors

Zhaoyang Liu

Zhaoyang Liu is a Shaanxi Normal University graduate student in the Department of Education. The research direction is the application of intelligent technology in education.

Wenlan Zhang

Wenlan Zhang is a professor of Shaanxi Normal University Education and a professor. Her research interests include educational applications of intelligent technology, project-based learning, and learning psychology and technology.

Liangliang Hu

Liangliang Hu is a Shaanxi Normal University phd candidate with a research interest in educational applications of artificial intelligence.

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