Individual PBL outcome effect sizes in the tutor-background meta-analysis span a massive range, from g = -1.26 to g = 1.91¶

Claim · All claims
Evidence · 1 study · quant-synthesis r2 · q2
Currency · newest study 2023 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Outcomes range from LeJeune (2002) at g = -1.26 to Ceconi (2006) at g = 1.91, alongside an overall modest effect of g = 0.27. → Walker 2023

Evidence¶

Walker 2023¶

Walker, A., & Leary, H. (2023). Conducting Problem-Based Learning Meta-Analysis: Complexities, Implications, and Best Practices. The Interdisciplinary Journal of Problem-based Learning. https://doi.org/10.14434/ijpbl.v17i2.35844

q2 · i? · quant-synthesis · r2

Forest plot of content-novice-tutor outcomes from Leary et al. (2013) (Figure 5), described in the Results text. The article reports the range quoted here and states the large variation and heterogeneity call for identification of systematic explanations and patterns.

"There is a massive range of outcomes from LeJeune (2002), g = -1.26, to the promising results of Ceconi (2006), g = 1.91."

Discussion¶

Related Claims¶

• Problem-based learning shows null or negative effects on basic knowledge acquisition but positive effects on conceptual understanding and transfer relative to direct instruction — the general claim this finding bears on, with the studies behind it
• The overall effect of PBL in the tutor-background meta-analysis is modest (g = 0.27) with large, statistically significant heterogeneity — related
• In a re-analysis of PBL tutor-background data, neither a meta-regression nor subgroup comparisons found that tutor expertise predicts student learning — related
• Funnel plot and Egger's test indicate publication bias in the PBL tutor-background data, and trim-and-fill suggests the overall effect is overestimated — related
• Robust variance estimation shows study of origin does not impact the final effect size in the PBL tutor-background data — related