Empirical Benchmarks for Planning and Interpreting Causal Effects of Community College Interventions

Abstract

Randomized controlled trials (RCTs) are an increasingly common research design for evaluating the effectiveness of community college (CC) interventions. However, when planning an RCT evaluation of a CC intervention, there is limited empirical information about what sized effects an intervention might reasonably achieve, which can lead to under- or over-powered studies. Relatedly, when interpreting results from an evaluation of a CC intervention, there is limited empirical information to contextualize the magnitude of an effect estimate relative to what sized effects have been observed in past evaluations. We provide empirical benchmarks to help with the planning and interpretation of community college evaluations. To do so, we present findings across well-executed RCTs of 39 CC interventions that are part of a unique dataset known as The Higher Education Randomized Controlled Trials (THE-RCT). The analyses include 21,163–65,604 students (depending on outcome and semester) enrolled in 44 institutions. Outcomes include enrollment, credits earned, and credential attainment. Effect size distributions are presented by outcome and semester. For example, across the interventions examined, the mean effect on cumulative credits earned after three semesters is 1.14 credits. Effects around 0.16 credits are at the 25th percentile of the distribution. Effects around 1.69 credits are at the 75th percentile of the distribution. This work begins to provide empirical benchmarks for planning and interpreting effects of CC evaluations. A public database with effect sizes is available to researchers (https://www.mdrc.org/the-rct-empirical-benchmarks).

Keywords

• empirical benchmarks
• effect size
• community college
• postsecondary
• enrollment
• credits