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TRUVACE RECORD VERSION
record: TRV-2026-2801
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:25:49.722109Z
status: published
lens: g_space
sector: health
headline: The effectiveness of GAI-assisted teaching methods in medical education: a systematic review and meta-analysis
dek: Objective The study evaluated the effectiveness of generative artificial intelligence (GAI)-assisted teaching methods on the medical educational outcomes. Methods Following the PRISMA guidelines, a systematic search was conducted for literature on AI-assisted educational interventions in medical education (e.g. clinical, nursing and dentistry medicine). PROSPERO registration number was CRD420251173150. Meta-analyses of the outcomes were performed using the Review Manager 5.4. Heterogeneity was evaluated using th…
gain_title: A meta-analysis of 78 controlled studies (3,635 students taught with generative AI, 3,931 controls) found higher knowledge scores (SMD 0.95) and practical scores (SMD 1.48) than traditional teaching in clinical, nursing and dental education.
problem_title: (none)
trace_subject: (none)
gain_reading: A meta-analysis of 78 controlled studies (3,635 students taught with generative AI, 3,931 controls) found higher knowledge scores (SMD 0.95) and practical scores (SMD 1.48) than traditional teaching in clinical, nursing and dental education.
gain_evidence: GAI-assisted teaching significantly improved academic performance in terms of both knowledge (SMD = 0.95, 95% CI: 0.72–1.18, p < 0.05) and practical (SMD = 1.48, 95% CI: 1.20–1.77, p < 0.05) scores
problem_reading: (none)
problem_evidence: (none)
quick_read: A systematic review and meta-analysis pooled 78 controlled studies of generative AI in medical education, covering 3,635 students in AI-assisted groups and 3,931 in control groups. Students taught with AI scored higher on knowledge exams (SMD 0.95) and practical assessments (SMD 1.48) than those taught by traditional methods.

Gains also appeared in student satisfaction (SMD 1.52), self-directed learning ability (1.25), clinical thinking ability (1.18) and analytical and problem-solving skills (1.53). Critical thinking skills showed no significant difference.

Results varied widely between studies (I2 of 94% for both main outcomes), and 51 of the 78 studies came from mainland China. Knowledge gains were concentrated among Asian students and late-phase clinical learners, with little effect in Europe and the Americas or in pre-clinical stages.
limitation: Results rest on highly heterogeneous studies, 51 of 78 from mainland China, and the authors found evidence of publication bias for the main knowledge and practical outcomes in Egger's test.
tag: Evidence-backed gain
key_points: The review searched English and Chinese databases from 2005 to 14 November 2025, screened 4,412 titles and abstracts, and included 78 studies; it was registered on PROSPERO (CRD420251173150). | The studies comprised 61 randomized trials and 17 non-randomized controlled trials, with clinical medicine (52 studies), nursing (17) and dental students (7). | Knowledge scores came from 57 studies (SMD 0.95); practical scores from 50 studies (SMD 1.48). | Binary outcomes favored AI-assisted teaching, with odds ratios from 3.50 to 10.97 for learning self-efficacy, initiative, self-directed learning, clinical thinking and problem-solving. | Critical thinking skills showed no significant difference (SMD 0.82, 95% CI −0.97 to 2.61, p = 0.37). | Of the randomized trials, 33 were rated low risk of bias, 25 some concern and 3 high risk; non-randomized studies were mostly medium quality (15 of 17). | ChatGPT was the named tool in 20 studies and self-developed AI platforms in 22; 14 studies did not name the tool.
rundown: The authors searched PubMed, Web of Science, ScienceDirect, Embase, the Cochrane Library and four Chinese databases. Included studies compared undergraduate medical, nursing and dental students taught with generative AI against students taught without it, and reported exam or practical scores.

Pooled effects were large but heterogeneity was high (I2 of 94% for both knowledge and practical scores). Subgroup analyses showed that region, student major, knowledge level and course content changed the size of the effect. AI-assisted learning in the late clinical phase produced higher knowledge (SMD 1.32) and practical scores (SMD 1.78), while pre-clinical effects were low.

Knowledge gains were seen among Asian students and not in courses in Europe and the Americas, while practical gains appeared in China, Europe and the Americas but little in other Asian regions. Of 78 studies, 40 were in English and 38 in Chinese, and 52 ran longer than one week.

The authors recommend that policymakers and education administrators integrate AI into teacher training and medical curriculum design, tailored to learners' knowledge level and specialism.
sources:
- peer_reviewed | Frontiers in Public Health | https://doi.org/10.3389/fpubh.2026.1813108 | 2026-04-22
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