Susanna Loeb

Susanna Loeb
Susanna Loeb
Principal Investigator,
Brown University

Susanna Loeb is the director of the Annenberg Institute and professor of education and international and public affairs at Brown University. Before moving to Brown, Dr. Loeb was the Barnett Family Professor of Education at Stanford University, where she was the founding director of the Center for Education Policy and co-director of Policy Analysis for California Education. Her research focuses broadly on education policy and its role in improving educational opportunities for students. Dr. Loeb's work has addressed issues of educator career choices and professional development, school finance and governance, and early childhood systems. She has been a member of the National Board for Education Sciences, a senior fellow at the Stanford Institute for Economic Policy Research, and a faculty research fellow at the National Bureau of Economic Research. She also led the research for both of the Getting Down to Facts projects for California schools and is co-author of the book Educational Goods: Values, Evidence, and Decision-Making. Dr. Loeb received a Ph.D. in economics from the University of Michigan.   

Publications by Susanna Loeb
While the importance of social-emotional learning for student success is well established, educators and researchers have less knowledge and agreement about which social-emotional skills are most important for students and how these skills…
Academic self-efficacy is a student’s belief in their ability to perform within a school environment. Prior research shows that students experience a drop in academic self-efficacy during middle school that is particularly steep for female students…
This brief applies value-added models to student surveys in the CORE Districts to explore whether social-emotional learning (SEL) surveys can be used to measure effective classroom-level supports for SEL. The authors find that classrooms differ in…
Existing research on self-management skills shows that measures of self- management predict student success. However, these conclusions are based on small samples or narrowly defined self-management measures. Using a rich longitudinal dataset of 221…