This brief describes the key findings from two randomized controlled trial studies of the Executive Development Program and paired coaching, designed to help principals improve their schools' instructional practices, climate, and student achievement.

The ultimate goal of every education intervention is to help enable students to achieve their fullest potential. Relatively few interventions suited for high schools are supported by evidence of positive effects. Research that is able to provide sound evidence about effectiveness is more important than ever.

Tools for Life®: Relationship-Building Solutions (TFL) is a program designed to improve school climate and safety through the proactive development of elementary and middle school students' interpersonal skills (relationship-building and communication) and intrapersonal skills (self-regulation and resiliency). In the 2016–2017 and 2017–2018 school years, the Jackson (Mississippi) Public School District (JPSD) implemented TFL in grades 1 through 8. RAND researchers conducted a randomized controlled trial to determine whether TFL, integrated into existing school practices, positively affected school climate and safety in the district. In this report, they describe the implementation of TFL in JPSD, calculate its costs, and evaluate the program's effectiveness.,TFL is designed to improve whole-school change in relationships among staff and students, but the authors found that implementation of TFL in JPSD schools was generally shallow, and the program was rarely, if at all, implemented across a whole school as it was designed. TFL had little impact: After one year of implementation, there were no practically or statistically significant differences between schools that implemented TFL and those that did not in measures of students' social and emotional, school climate, behavioral, or achievement outcomes. In addition to the uneven implementation of the program, the authors discuss how methodological limitations of the study and contextual factors in JPSD may have contributed to these findings.

Demands for scientific knowledge of what works in educational policy and practice has driven interest in quantitative investigations of educational outcomes, and randomized controlled trials (RCTs) have proliferated under these conditions. In educational settings, even when individuals are randomized, both experimental and control students are often grouped into particular classrooms and schools and share common learning experiences. Analyses that account for these clusters are common. A less common design involves one clustered experimental arm and one unclustered experimental arm, sometimes called a partially clustered design. Analysts do not always use methods that yield valid statistical inferences for such partially clustered designs. Additionally, published methods for handling partially clustered designs may not be flexible enough to handle real-world complications, including treatment non-compliance. In this paper, we illustrate how models that accommodate partial clustering may be used in educational research. We explore the performance of these models using a series of Monte Carlo simulations informed by data taken from a large-scale RCT studying the impacts of a programme designed to decrease summer learning loss. We find that clustering and non-compliance can have substantial impacts on statistical inferences about intent-to-treat effects, and demonstrate methods that show promise for addressing these complications.