Essays in College Course-Taking
Hsu, Julian
2017
Abstract
While college major choices are consequential, students do not know their capacity to perform in academic and non-academic environments related to those majors, and may not be prepared to take the classes for those majors. In my dissertation, I use detailed course transcript data to understand how students explore different majors and the roles of current and future college policies. In my first chapter, Learning about College Major Match: Microfoundations from Dynamic Course-Taking, I develop and estimate an economic model to understand how first year courses can set students onto the path to their major. I develop and estimate a structural dynamic course-taking model that highlights how students learn about major match quality and complete course requirements to graduate in different majors. The model highlights how the breadth and depth of coursetaking across and within majors affects graduating major and graduation time. Estimating my model, I simulate a policy requiring students to take a variety of courses across different majors during their first year. As a more rigorous version of current colleges' distributional course requirements, this counterfactual policy causes the share of Natural Science graduates to increase ten percentage points. I find this counterfactual causes additional path dependence in the Natural Sciences from completing course requirements, rather than providing additional information. My second chapter, Do Grades Matter? Evidence from College Transcripts, complements the first and dives into the correspondence between courses and majors. I combine administrative transcript data from a large public four-year institution to create a novel measurement of how student's progress in majors' course requirements. I find that four semesters after declaring one major, all students complete between 15% to 25% of the course requirements necessary to graduate in the Humanities, Social Sciences, and Psychology. Students' course-taking also seem to respond to first year grades. I construct a dynamic course-taking model, where in students take courses to learn about major abilities and complete majors' course requirements. The transcript data is consistent with the model's result that major switching costs increase as they continue to complete the course requirements in one major. The third chapter, Math for All? Regression Discontinuity in Signals of Preparation for College Quantitative Coursework (with William J. Gehring), uses plausibly exogenous variation to evaluate how higher education institutions can influence student course-taking and major choice. College calculus courses can be a stumbling block in pursuit of some goals for under-prepared students. We study how student course-taking and major decisions at an elite public institution respond to recommendations to take Pre-Calculus or Calculus. Using a regression discontinuity framework to estimate Intent-to-Treat effects, we find that, among the least-prepared students, students with a tentative recommendation to take Pre-Calculus are 60% more likely to ever take Calculus than if they receive a definite recommendation to take Pre-Calculus. We find suggestive evidence these recommendations equalize course-taking and major completion outcomes in Economics, Statistics, Biology, and Chemistry. We do find, however, evidence that students with the least favorable recommendation are more likely to be diverted toward quantitative courses that do not count toward a major. Our work suggests inducing students to take Pre-Calculus or Calculus is insufficient to encourage them into quantitative majors.Subjects
College Major Course-Taking
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