Effectiveness of AI- and VR-based simulation with traditional teaching in healthcare education: a network meta-analysis
Abstract
Aims (i) To summarize the application scenarios and teaching models of AI and VR in healthcare education. (ii) To compare teaching outcomes between AI, VR, and traditional methods. (iii) To identify the relative advantages of AI and VR in different outcomes.Design A network meta-analysis.Data sources We systematically searched ten databases, including PubMed, Embase, Web of Science, Cochrane Library, IEEE Xplore, CINAHL, Association for Computing Machinery, China National Knowledge Infrastructure, WanFang, and China Computer Federation, to identify randomized controlled trials and quasi-experimental studies.Methods Educational effects of various teaching methods were compared through network meta-analysis by estimating standardized mean differences (SMD) with 95% confidence intervals (CIs). Study quality was evaluated using the Joanna Briggs Institute Critical Appraisal Tool.Results This study included 54 studies. The network meta-analysis results showed that in nursing education, VR, compared to traditional teaching, improved students' satisfaction (SMD = 0.93, 95% CI: 0.07 to 1.80), knowledge (SMD = 0.60, 95% CI: 0.30 to 0.90), and practical skills (SMD = 1.06, 95% CI: 0.57 to 1.55), while AI only enhanced knowledge (SMD = 1.11, 95% CI: 0.60 to 1.62). There was no significant difference in the indirect comparison between AI and VR. In clinical medicine, both VR and AI improved knowledge (VR: SMD = 0.75, 95% CI: 0.32 to 1.19; AI: SMD = 0.81, 95% CI: 0.10 to 1.51) and practical skills (VR: SMD = 1.14, 95% CI: 0.65 to 1.63; AI: SMD = 0.91, 95% CI: 0.16 to 1.66) compared to traditional teaching, but no significant difference was found in the indirect comparison between AI and VR.Conclusions Future research should focus on direct comparisons between AI and VR, assess their long-term educational effects, and design integrated teaching models that harness the strengths of both technologies to inform evidence-based improvements in instructional practice.Registration (PROSPERO): CRD42024605827.
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A network meta-analysis in nursing education revealed that AI simulation was highly effective in enhancing knowledge acquisition (standardized mean difference=1.11).
“Furthermore, a network meta-analysis in nursing education revealed that while AI simulation was highly effective in enhancing knowledge acquisition (standardized mean difference=1.11), its effect on cultivating practical skills was relatively limited [61].”
From AI-Powered Simulation for Nursing Education: Mixed Methods Systematic Review (2026) · cites this paper as [61]
AI simulation's effect on cultivating practical skills was relatively limited.
“Furthermore, a network meta-analysis in nursing education revealed that while AI simulation was highly effective in enhancing knowledge acquisition (standardized mean difference=1.11), its effect on cultivating practical skills was relatively limited [61].”
From AI-Powered Simulation for Nursing Education: Mixed Methods Systematic Review (2026) · cites this paper as [61]
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- Authors
- Wang, M., Xiao, L., Jiao, J., Sun, M., Ni, Z., Xiao, J., Tan, M., Zhang, H., Liu, W., & Ding, J.
- Affiliations
- Central South University (CN)
- Southern Medical University (CN)
- Yale University (US)
- Corresponding author
- Liu, Wei
- Ding, Jinfeng
- Venue
- Nurse Education Today
- Publisher
- Elsevier BV
- Published
- 2026-05
- Volume
- 160
- Pages
- 107008
- ISSN
- 0260-6917 (ISSN-L)
- OpenAlex
- W7125612633
- Cited by
- 6
- References
- 47
- Citations by year
- 2026: 6
- FWCI
- 6.27
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nurse Education Today (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Central South University (2025ZZTS0864)
- Topics
- Health Sciences › Medicine › Physiology › Simulation-Based Education in Healthcare
- Health Sciences › Medicine › Surgery › Surgical Simulation and Training
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Keywords
- artificial intelligence in education, virtual reality, simulation-based training, healthcare education, nursing education, clinical medicine education, conventional instruction comparison, student satisfaction, knowledge acquisition, practical skills, teaching methods comparison, teaching model, integrated teaching model, educational technology effectiveness
- MeSH terms
- Simulation Training, Virtual Reality, Artificial Intelligence, Education, Nursing, Humans, Teaching
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