Assess the learner's ability to analyze methodological biases and effect heterogeneity in randomized controlled trials of K–12 educational interventions. Items will probe identification and consequences of selection, attrition, measurement, implementation, and spillover biases; design features like clustering and randomization unit; statistical approaches for detecting and estimating heterogeneous treatment effects (e.g., interaction models, multilevel models, causal forests); diagnostic checks, sensitivity analyses, ITT vs CACE estimands, power considerations for subgroup analysis, and implications for interpretation and policy.