Measuring Students’ Social-Emotional Learning Among California’s CORE Districts

An IRT Modeling Approach
Robert H. Meyer
Education Analytics
Caroline Wang
Education Analytics
Andrew Rice
Education Analytics


With an increased appreciation of students’ social-emotional skills among researchers and policy makers, many states and school districts are moving toward a systematic process to measure Social-Emotional Learning (SEL). In this study, we examine the measurement properties of California's CORE Districts’ SEL survey administered to over 400,000 students in grades 3 to 12 during the 2015-16 school year. We conduct analyses through both classical test theory and item response theory frameworks, applying three different polytomous IRT models on both the full student sample and on separate samples from each grade. From these analyses, we summarize the psychometric properties of items at each grade level, compare items' functionality across grades, compare student outcomes from IRT models and the classical approach, make suggestions on approaches to modeling and scaling the SEL survey data, and identify items, by grade, that do not contribute positively to measurement of each outcome. Finally, we discuss policy implications in using SEL measures among educators, administrators, policy makers, and other stakeholders.

Suggested citationMeyer, R. H., Wang, C., & Rice, A. (2018, May). Measuring students’ social-emotional learning among California’s CORE districts: An IRT modeling approach [Working paper]. Policy Analysis for California Education.