Topic-wise gains were heterogeneous, with some topics showing no meaningful change¶

Claim · All claims
Evidence · 1 study · causal r1 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Exploratory topic-level gains ranged widely; at Centre 2, CVD improved 16.1% and HIV 15.8%, while IDA showed no meaningful change (0.3%, p = 0.947). → Joshi U 2026

Evidence¶

Joshi U 2026¶

Joshi U, Sarkar A, Shukla A, Shrimali S, Bezbaruah NK, B Sanjay Kini, Baisil S, Sheth Z, Bhargava P, Shah S. (2026). Ears for examinations: a multicentre quasi-experimental evaluation of AI-generated revision podcasts on learning outcomes and retention among medical students. BMC Medical Education. https://doi.org/10.1186/s12909-026-10080-6

q2 · i? · causal · r1

Exploratory topic-wise paired analyses (Table 5), 10 items per topic, Holm-adjusted across six topics per centre. The quoted sentence prints percentage gains and p-values but no effect size, so impact is uncoded. At Centre 1 the largest improvements were HIV (12.9%) and HTN (8.8%).

"At Centre 2, improvements were seen across most topics (e.g., CVD 16.1%, Holm-adjusted p = 0.022; HIV 15.8%, Holm-adjusted p = 0.003), while IDA showed no meaningful change (0.3%, Holm-adjusted p = 0.947)."

Discussion¶

Related Claims¶

• AI-generated revision podcasts produce statistically significant immediate learning gains in medical students at both study centres — related
• Learners valued AI revision podcasts for portability and 'dead time' use but identified absent pauses and AI voice monotony as design barriers — related
• Retention trajectories diverged by centre: Centre 1 retained gains at 30 days while Centre 2 showed significant post-to-delayed decay — related
• Podcast gains extend beyond recall to higher-order application and analysis items at both centres — related
• Heterogeneous learning curves across practitioners create organizational challenges including perceived unfairness — related
• Warning effect size shows no significant heterogeneity across topics and studies — related