Introduction: The What Works Clearinghouse (WWC) reviews rigorous research on educational interventions with a goal of identifying "what works" and making that information accessible to educators and policymakers. In rating the quality of causal research, the WWC has historically prioritized internal validity over external validity. One…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

Data Envelopment Analysis (DEA) is a widely adopted non-parametric technique for evaluating R&D performance. However, traditional DEA models often struggle to provide reliable solutions in the presence of data uncertainty. To address this limitation, this study develops a novel robust super-efficiency DEA approach to evaluate R&D…

The STEM.LD program was funded by a 2020 mid-phase Education Innovation and Research (EIR) grant. It sought to improve student outcomes by strengthening professional learning for teachers and school leaders, expanding STEM curricular resources, and increasing student engagement in rigorous coursework and extracurricular opportunities. A randomized…