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Effectiveness of generative artificial intelligence-based teaching versus traditional teaching methods in medical education: a meta-analysis of randomized controlled trials
- Truvace record
- TRV-2026-2832raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Systematic review or meta-analysis
- Sources
- 1 sourcePeer-reviewed
- sha256
- 1b3d87b50007…check it
BACKGROUND: Artificial intelligence (AI) has demonstrated remarkable capabilities across diverse medical applications, potentially revolutionizing healthcare delivery systems. This systematic review and meta-analysis investigated the comparative effectiveness of generative artificial intelligence (GAI)-based teaching methodologies versus conventional pedagogical approaches on educational outcomes among medical students. METHODS: We conducted a comprehensive literature search across multiple electronic databases,…
61Gain side
How the two sides scoreClose call
60Problem side
The gain
A meta-analysis of two randomized trials (103 medical students) found generative AI teaching produced higher practical skill scores than traditional teaching (SMD 0.63, 95% CI 0.10 to 1.16).
The problem
A meta-analysis of 11 randomized trials with 786 medical students found no significant knowledge-score difference between generative AI teaching and traditional teaching (SMD 0.27, 95% CI -0.31 to 0.85), with low-quality evidence.
A fixed formula sets both scores from the evidence and its sources. Reader votes don’t move them.
What the scores mean
G is the gain side, out of 100. It goes up when the gain is specific, when it measurably helped people and when the sources behind it are strong.
P is the problem side, out of 100. It goes up when the problem is specific, when it measurably hurt people and when the sources behind it are strong.
What this doesn’t fix
The authors say statistical power may be limited by the small number of studies and modest sample sizes, substantial heterogeneity remained, and many trials poorly documented randomization and blinding.
Sources
1 on file- BMC Medical Educationdoi:10.1186/s12909-025-07750-2
What the review found when it combined the studies
These are the review’s own pooled results, copied from its abstract. Truvace did not recalculate them.
Medical students' practical skill scores with generative AI teaching compared with traditional teaching
SMD 0.63 (95% CI 0.10 to 1.16)
2 studies · search to January 2025
The review’s own words
Additionally, the meta-analysis, which involved only two studies (52 GAI-based students and 51 traditional teaching students), showed that the GAI-based teaching had significantly higher skill scores compared to the traditional teaching method (SMD 0.63, 95% CI 0.10 to 1.16; p = 0.02; I² = 43%; Fig. 3 ), under the random-effects model.
Medical students' teaching satisfaction with generative AI teaching compared with traditional teaching
SMD 1.18 (95% CI 0.50 to 1.87)
search to January 2025
The review’s own words
There were three studies conducted on the survey on teaching satisfaction in both student groups, and the GAI group reported higher satisfaction than the traditional group (SMD 1.18, 95% CI 0.50 to 1.87; p < 0.01; I² = 79%; Fig. 3 ), with the difference being statistically significant.
Medical students' knowledge scores with generative AI teaching compared with traditional teaching
SMD 0.27 (95% CI −0.31 to 0.85)
11 studies · 786 people · search to January 2025
The review’s own words
Meta-analysis with a random-effects model showed that there was no significant difference in knowledge scores between the groups (SMD 0.27, 95% CI −0.31 to 0.85; p = 0.36; I² = 93%; Fig. 3 ).
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Cite this record
v1Truvace Impact Record TRV-2026-2832, v1: “Effectiveness of generative artificial intelligence-based teaching versus traditional teaching methods in medical education: a meta-analysis of randomized controlled trials.” Truvace, 2026-11-12. /record/TRV-2026-2832 (accessed on the day you copy it). sha256 1b3d87b50007ff71…
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