Insights into Social-Emotional Learning and Achievement: An Approach for Strengthening Causal Inference

Meghan McCormick

Social Emotional Learning (SEL) programs aim to support social-emotional skill development (e.g., behavioral/emotional regulation, attention) to improve children?s academic achievement. Given research showing that children growing up in poverty start school with lower levels of social-emotional skills, integration of SEL programs into traditional instruction may help close achievement gaps. Yet, evaluations of SEL programs have had mixed results, with some programs showing positive impacts and others having no effects on achievement. It is difficult to understand these mixed findings because few studies have examined how SEL programs work, and the types of settings and conditions that best support their implementation. Using the SEL program INSIGHTS as a case study, this dissertation will employ causal modeling to test not only whether the program effected academic achievement, but also how, where, and under what circumstances. The project uses a) instrumental variables and principal score matching to test classroom level mechanisms of INSIGHTS on achievement; b) multi-level modeling to examine differential effects of INSIGHTS by dimensions of school climate; and c) principal score matching to test program dosage effects. Given recent efforts by policymakers, practitioners, and parents to integrate social emotional skill development into schooling, there is more investment in SEL programs than ever. However, sustainable educational change must be built on rigorous research that allows for causal inference. Given the climate of limited resources, this dissertation will help policymakers identify effective programs, determine outcomes that measure program efficacy, and target critical conditions for change in school contexts.

About Meghan McCormick

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