Students report generally high satisfaction with AI-powered PBL/CBL¶

Claim · All claims
Evidence · 1 study · quant-synthesis r1 · q3
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? Meta-analysis of three studies (74 participants) found a pooled standardised mean satisfaction score of 0.7 (95% CIs [0.47-0.92]), statistically significant (Z = 6, P < 0.0001). → Wei H 2025

Evidence¶

Wei H 2025¶

Wei H, Dai Y, Yuan K, Li KY, Hung KF, Hu EM, Lee AHC, Chang JWW, Zhang C, Li X. (2025). AI-Powered Problem- and Case-based Learning in Medical and Dental Education: A Systematic Review and Meta-analysis. International Dental Journal. https://doi.org/10.1016/j.identj.2025.100858

q3 · i? · quant-synthesis · r1

Meta-analysis of satisfaction questionnaires from three RCTs answered only by AI-group students (74 participants total); moderate heterogeneity (I² = 32%), fixed-effect generic inverse variance method; overall effect significant (Z = 6, P < 0.0001). No standardised effect size was printed.

"The pooled SM satisfaction score was 0.7 (95% Cls [0.47-0.92]), indicating students were generally satisfied with AI-assisted PBL/CBL, and the variability in the satisfaction score across 3 studies was moderate."

Discussion¶

Related Claims¶

• Evidence for AI-powered PBL/CBL is limited: small study count, some concerns risk of bias, and no long-term effectiveness data — related
• No included studies applied AI-based modalities specifically to public health education, though external reviews report positive satisfaction with AI-assisted PBL and CBL — possibly the same claim (merge candidate)
• Students were generally satisfied with the PBL approach across the included studies — related