Susanna Loeb
King Center on Global Development
Professor
Graduate School of Education
Senior Fellow
Stanford Institute for Economic Policy Research (SIEPR)
Susanna Loeb is a Professor at the Graduate School of Education. She was Director of the Annenberg Institute at Brown University, where she was also Professor of Education and of International and Public Affairs and the founder and acting executive director of the National Student Support Accelerator, which aims to expand access to relationship-based, high-impact tutoring in response to the Covid-19 pandemic. Susanna’s research focuses broadly on education policy and its role in improving educational opportunities for students. Her work has addressed issues of educator career choices and professional development, of school finance and governance, and of early childhood systems. Before moving to Brown, Susanna was the Barnett Family Professor of Education at Stanford. She was the founding director of the Center for Education Policy at Stanford and co-director of Policy Analysis for California Education. Susanna led the research for both Getting Down to Facts projects for California schools. In 2020, she was elected to the American Academy of Arts and Sciences. She is also an affiliate at NBER and JPAL and a member of the National Academy of Education.
King Center Supported Research
2024 - 2025 Academic Year | Global Development Research Funding Grant
AI’s Got Talent: Unlocking the STEM Innovation Pipeline in Under-Resourced Settings
This project examines whether generative AI can expand the STEM innovation pipeline by reducing frictions in idea development and problem-solving. In a randomized trial with 4,000 female engineering students in India, we test whether access to GenAI shifts behavior on the extensive and intensive margins of innovation. The intervention embeds AI tools into an applied curriculum, culminating in a hackathon evaluated on novelty, feasibility, and impact. We combine survey, behavioral, and log data to track changes in skill acquisition and exploratory problem-solving. The study provides evidence on how AI access shapes the production of innovation in resource-constrained settings.