The Higher-Ed Coronavirus Response in the Public Sector

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Using a combination of data from the College Crisis Initiative (C2i), the Integrated Postsecondary Data System (IPEDS), and CDC coronavirus statistics, this paper investigates the factors which play significant roles in predicting Fall 2020 mode of instruction in the public, 4-year sector of higher education. Using principal components analysis (PCA), I am able to scale down nearly 30 institutional features to a handful of orthogonal vectors while maintaining relatively high predictive accuracy. Further, I find that the primary factors in predicting in-person instruction were state political leaning and intercollegiate athletics.

Working paper can be downloaded here.

Adam Hearn
Data Scientist, Researcher, Higher-Education Advocate

I am a Data Scientist at the American Institutes for Research, one of the world’s largest non-profit social science research centers.