My research interests center on college access, the outcomes of college participation, and using tools of data science such as machine learning and Bayesian statistics to critically examine higher education policy questions that are difficult to answer with conventional econometric tools.
In my work I have examined how students weigh factors like distance and cost when choosing a college and the effect of college participation on both economic outcomes and civic behaviors. I have also used poststratification techniques to improve the representativeness of survey responses among former students who exited early and to produce state-level estimates of low-income college enrollment using non-representative data. I have a particular interest in students’ access to broadband: how it varies across student populations, its connection to past housing policy, and its relationship to online course enrollments. See my publications and working papers pages for a complete list of my papers and my GitHub profile for links to replication files for many of my projects.
I am the author and maintainer of a number of software packages, including rscorecard, which can be used to download data from the College Scorecard; crosswalkr, a port of a set of Stata commands that help build primary data sets from smaller files in a reproducible manner; duawranglr, a set of functions to help users create shareable data sets from protected data files according to a data use agreement; and GitRoom Manager, a program that allows instructors to more easily manage a GitHub-based virtual classroom from the command line. Other small scripts that I share can be found on my code page.
I earned my doctorate in leadership and policy studies from Vanderbilt University in 2017, master’s in the humanities from the University of Chicago in 2008, and bachelor’s in music and English from Vanderbilt in 2006.