Meta-Analysis Results on Generative AI-Assisted Teaching in Medical Education

78 studies involving 7,566 medical students were analyzed in a systematic review and meta-analysis. The pooled results show generative AI-assisted teaching significantly improved academic performance, student satisfaction, and various learning skills. The dataset, last updated in April 2026, contains the statistical results from this meta-analysis.

Use Cases

• Compare effect sizes for knowledge versus practical skill improvement based on the reported standardized mean differences (SMDs).
• Assess the impact of GAI on student satisfaction and self-efficacy based on the meta-analysis results.
• Evaluate publication bias and heterogeneity in educational intervention studies using the described statistical methods.
• Inform curriculum design and teacher training by analyzing the pooled outcomes across multiple studies.

Strengths

• Results are derived from a systematic review of 78 studies following PRISMA guidelines.
• Analysis includes data from 7,566 medical students (3,635 in intervention, 3,931 in control).
• Effect sizes are provided for multiple outcome measures, including knowledge, practical skills, and soft skills.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain analytical tasks.
• The dataset is small (29.3 KB), suggesting it contains summary statistics rather than raw study data.

Provenance

Source

figshare, author Xingming Ma.

Collection Method

Systematic review and meta-analysis conducted following PRISMA guidelines, using Review Manager 5.4.

Time Range

Temporal coverage of the included studies is not specified.

Freshness

Last updated 2026-04-22 05:46:37; freshness should be verified.

Geography

Spatial coverage of the included studies is not specified.