Type: Seminar

Technology adoption in education: Spillovers, intensity and student achievement

Date & Time

Feb 11, 2015, 8:30-10:30 am EST

Location

Weill Hall, Room 3240
735 S. State Street, Ann Arbor, MI 48109

Open to PhD students and faculty engaged in causal inference in education research.

From the speaker's bio:

Peter Bergman is an assistant professor of economics and education at Teachers College, Columbia University. He earned his PhD in economics from the University of California, Los Angeles. He earned his BA from the University of California, Berkeley. His research focuses on field experiments designed to improve financial and educational outcomes for low-income families. Bergman’s research has involved field experiments providing translated text messages to families about their child's academic progress, for which he won the Distinguished CESifo Affiliate Award. His current interests in higher education include studying the returns to STEM-related degrees, testing strategies to improve take up of education-related tax-benefits, and assessing the effects of these benefits on student outcomes. Previously, Bergman was an associate economist at RAND, an advisory board member to the Partnership of Los Angeles Schools, and a New York City Teaching Fellow as a middle school special education teacher.

About CIERS:

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.