A talk by Steven Hemelt, University of North Carolina - Chapel Hill
Open to PhD students and faculty engaged in causal inference in education research.
From the speaker's bio:
Steven Hemelt is assistant professor of public policy at the University of North Carolina – Chapel Hill. Prior to joining the faculty at UNC, Hemelt was an IES postdoctoral research fellow at the Gerald R. Ford School of Public Policy. His fields of interest include education policy, economics of education, labor economics, and program evaluation. In one strand of current research, Hemelt is examining the effects of different policies or programs on students’ performance in high school, transition into college, and longer-run college outcomes (e.g., persistence, credit accumulation, and graduation). In a second line of work, he is exploring the impacts of K-12 accountability structures, consequences, and supports on a variety of student outcomes. In the past, Hemelt has studied the impacts of failure to make “adequate yearly progress” (AYP) under No Child Left Behind (NCLB) on subsequent student achievement, the effects of additional learning time on student performance, and the usefulness of college double majors in the labor market. Hemelt earned his PhD in Public Policy from the University of Maryland, Baltimore County (UMBC). He holds a master's and undergraduate degree in economics and a bachelor's degree in Spanish.
The objective of the Causal Inference in Education Research Seminar (CIERS) is to engage students and faculty from across the university in conversations around education research using various research methodologies.
This seminar provides a space for doctoral students and faculty from the School of Education, Ford School of Public Policy, and the Departments of Economics, Sociology, Statistics, and Political Science to discuss current research and receive feedback on works-in-progress. Discourse between these schools and departments creates a more complete community of education scholars, and provides a networking opportunity for students enrolled in a variety of academic programs who share common research interests. Open to PhD students and faculty engaged in causal inference in education research.