What Impacts Should We Expect from Tutoring at Scale? Exploring Meta-Analytic Generalizability

October 2024

U.S. public schools are engaged in an unprecedented effort to expand tutoring in the wake of the pandemic. Broad-based support for scaling tutoring emerged, in part, because of the large effects on student achievement found in prior meta-analyses. We conduct an expanded meta-analysis of 282 randomized control trials and explore how estimates change when we better align our sample with a policy-relevant target of inference: large-scale tutoring programs in the U.S. aiming to improve standardized test performance. Pooled effect sizes from studies with stronger target-equivalence remain meaningful, but are only a third to a half as large as those from our full sample. This result is driven by stark declines in pooled effect sizes as tutoring program scale increases. We explore four hypotheses for this pattern and identify a bundled package of design features that our analyses suggest may help to partially inoculate programs from these attenuated effects at scale.

Keywords

Tutoring, Scaling, COVID-19, Meta-Analysis, Achievement

Education level

K-12 Education

Topics

Methods