Small World Student Network at the University of Texas at Dallas in Times of Social Distancing
Kailash Subramanian, Joshua M. Williams, Daniel C. DeAnda, Aditya A., Agrawal, Andrei Racila, Aditi R. Prabhu, Lawrence Redlinger, Christopher, Wendt, Ravi Prakash

TL;DR
This study analyzes university enrollment networks during social distancing, revealing small-world properties and suggesting targeted policies to reduce infectious spread while considering academic and financial factors.
Contribution
It identifies the small-world structure of student networks and proposes targeted instructional policies to mitigate disease transmission in higher education settings.
Findings
Enrollment networks are small worlds with high clustering and short paths.
Connectivity decreases with higher class standing and course level.
Targeted policies can reduce infection risk while maintaining educational objectives.
Abstract
To limit the spread of the novel coronavirus on college campuses, a common strategy for the Fall 2020 and Spring 2021 terms has been to offer instruction weighted toward hybrid or fully online modalities. Colleges are now considering whether and how to expand hybrid or fully in-person instruction for future terms, and learn lessons from this experience for future use. Our paper uses Fall 2019 enrollment data for a medium-sized public American university to analyze whether some student groupings by class standing or course level are more susceptible to the spread of infectious disease through academic enrollment networks. Replicating Weeden and Cornwell [8], we find that enrollment networks at the institution are "small worlds" characterized by high clustering, short average path lengths, and multiple independent connections. Connectivity decreases as class standing (graduate vs.…
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Taxonomy
TopicsHigher Education Research Studies · Service-Learning and Community Engagement
