Presented By: Causal Inference in Education Research Seminar (CIERS)
Causal Inference in Education Research Seminar (CIERS)
Math for All? Evidence from Regression Discontinuities in College Math Recommendations presented by Julian Hsu, University of Michigan
Abstract:
Although higher education institutions focus on helping all students succeed, there is limited work on how institution-wide policies affect student outcomes. In this paper we use a regression discontinuity framework to estimate the causal impacts of college math recommendations. Our setting and recommendation system significantly differ from that in the developmental course literature. We use transcript data to find variation in the persistent of effects on taking Calculus, and temporary effects in quantitative course-work. We also identify substitutes for quantitative course-work, what subjects students substitute with STEM or quantitative majors.
Although higher education institutions focus on helping all students succeed, there is limited work on how institution-wide policies affect student outcomes. In this paper we use a regression discontinuity framework to estimate the causal impacts of college math recommendations. Our setting and recommendation system significantly differ from that in the developmental course literature. We use transcript data to find variation in the persistent of effects on taking Calculus, and temporary effects in quantitative course-work. We also identify substitutes for quantitative course-work, what subjects students substitute with STEM or quantitative majors.
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