Degree: Ed.D., Harvard Univesity, (2016)
Faculty Assistant: Cindy Floyd
David Blazar is a postdoctoral fellow at the Center for Education Policy Research at the Harvard Graduate School of Education (HGSE). Blazars research and teaching interests include education policy analysis and applied quantitative research to support causal inferences, focusing in particular on organizational change in K-12 public schools and policies to support both teacher and teaching quality. His work in this area has been published in American Educational Research Journal, Economics of Education Review, Educational Evaluation and Policy Analysis, Educational Researcher, and other journals. In 2015, he was a summer fellow with Mathematica Policy Research, where he conducted research for his dissertation on the relationship between teachers, teaching, and student outcomes beyond test scores. Previously, he taught high-school English Language Arts in New York City. He holds a BA in history and literature from Harvard College, as well as an EdM in policy and management and a doctorate in quantitative policy analysis in education, both from HGSE.
A growing body of evidence identifies a range of academic behaviors other than test scores, including disruptive behavior, self-efficacy, and happiness, as important contributors to childrens long-term success in the labor market and beyond. A handful of studies further indicate that teachers play an important role in developing non-tested outcomes. Additional research that validates these measures of teacher effectiveness on non-tested outcomes would have important implications not only for teacher recruitment, assessment, and placement, but also for improving overall life trajectories of students.
In this study, we propose two complementary lines of research that explore the relationship between teachers and students non-tested outcomes. First, we will measure whether teachers can have effects on non-tested outcomes. This is possible because we will make use of a unique, pre-existing dataset in which class rosters were randomly assigned to teachers within schools. This design will allow us to test whether teachers who were observed as effective at raising non-tested outcomes prior to random assignment produce higher outcomes following random assignment.
Second, we will examine whether teachers effects on upper elementary students non-tested outcomes persist or fade out over time. This is important because it will tie measured increases in student progress on non-tested outcomes to actual behaviors that are of interest to school officials and policy makers. To do so, we will collect additional administrative data on students at the end of middle school and beginning of high school. Drawing on the same data, we will examine whether self-reported measures of students non-tested outcomes predict related school behaviors (e.g., absences, suspensions, on-time grade progression, GPA) in subsequent years.