Jennifer Sloan McCombs

Standards-Based Accountability under No Child Left Behind: Experiences of Teachers and Administrators in Three States. MG-589-NSF.

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How Instructional Coaches Support Data-Driven Decision Making: Policy Implementation and Effects in Florida Middle Schools.

This article examines the convergence of two popular school improvement policies: instructional coaching and data-driven decision making (DDDM). Drawing on a mixed methods study of a statewide reading coach program in Florida middle schools, the article examines how coaches support DDDM and how this support relates to student and teacher outcomes. Authors find that although the majority of coaches spent time helping teachers analyze student data to guide instruction, data support was one among many coach activities. Estimates from models indicate that data analysis support, nevertheless, has a significant association with both perceived improvements in teaching and higher student achievement.

Linking Reading Coaches and Student Achievement: Evidence From Florida Middle Schools

Many policymakers suggest that school-based reading coaches can improve teachers’ practice, which consequently will improve students’ literacy skills. Although reading coaches are increasingly prevalent in schools nationwide, empirical evidence for their effects on student achievement is scarce. This article helps to address this gap by conducting an evaluation of a statewide reading coach program in Florida middle schools. Using achievement data from nearly 1,000 Florida middle schools from the 1997–1998 through 2005–2006 school years, we find that receiving a state-funded coach was associated with statistically significant improvements in average annual reading achievement gains for two of the four cohorts of schools analyzed. We examine implications for state and district policy and future research.

Reading Coach Quality: Findings from Florida Middle Schools

Drawing on a statewide study of Florida middle-school reading coaches, this article examines what constitutes, contributes to, and is associated with high-quality coaches and coaching. Authors find that coaches generally held many of the qualifications recommended by state and national experts and principals and teachers rated their coaches highly on many indicators of quality. However, several common concerns about recruiting, retaining, and supporting high-quality coaches emerged. Estimates from models indicate that a few indicators of coach experience, knowledge, and skills had significant associations with perceived improvements in teaching and higher student achievement, although the magnitude of the latter relationship was quite small. Findings suggest that although possessing strong reading knowledge and instructional expertise may be important for coaching, it may not be sufficient.

Using State School Accountability Data to Evaluate Federal Programs: A Long Uphill Road

Evaluations of federal programs designed to improve student achievement generally depend on data gathered by the states for school accountability purposes, rather than data specifically designed for program evaluation. In addition, these data are available at the school level but not at the student level. This article first discusses issues related to the quality of school-level data collected as part of state accountability systems, including the reliability and validity of school-level test scores as a measure of the value added by schools to student learning. It then outlines various ways in which school-level data can be usefully analyzed and illustrates the challenges inherent in doing so, including the challenges of aggregating data across states to find an overall program effect. The final section discusses the implications of the arguments presented here for measuring changes in school performance and linking these effects to a specific program. Ultimately, our ability to measure changes in outcomes and link them back to the intervention depends on three factors: (a) identifying a set of activities attributable to the program, (b) measuring the quality of implementation of these activities, and (c) obtaining a valid and reliable measure of the desired outcome. The article makes it clear that none of these is easy to come by.

Study Suggests: Kids Who Attend More Thrive More

Excerpted from Learning from Summer: Effects of Voluntary Summer Learning Programs on Low-Income Urban Youth, Catherine H. Augustine et al., RAND Corporation, RR-1557, 2016. The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities throughout the world safer and more secure, healthier and more prosperous. RAND is nonprofit, nonpartisan, and committed to the public interest. www.rand.org/t/RR1557 These findings are correlational but very likely due to the summer learning programs. The differences in the performance between the “high attenders” and the control group are the equivalent of about 20%–25% of a year’s learning in language arts and math at this age. These benefits persisted throughout the 5th-grade school year. Kids with high attendance performed better in math and reading after two summers compared with students in the control group, who were not invited to participate in the programs.