Human instruction versus machine learning: Scaling up policy interventions to reduce inequality in college access | Gerald R. Ford School of Public Policy
Type: Seminar

Human instruction versus machine learning: Scaling up policy interventions to reduce inequality in college access

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

Speaker

Xiaoyang Ye, PhD Student in Higher Education

Date & time

Aug 14, 2018, 8:30-10:00 am EDT

Location

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 social science disciplines to discuss current research and receive feedback on works-in-progress. Discourse across 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.

Our regular meeting schedule is Wednesday mornings from 8:30 to 10 am in Weill 3240. Check out our website to learn more and to sign up for the mailing list.