Examining the decision to offer in-person college instruction during the COVID-19 era: A multilevel analysis of the factors that affected intentions to open
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Abstract
At the end of Summer 2020 colleges and universities had to make difficult decisions about whether to return to in-person instruction. While opening campuses could pose a major health risk, keeping instruction online could dissuade students from enrolling. Taking an ecological approach that considers the influence of state, county, and college characteristics, this study uses mixed modeling techniques and data from 89% of two- and four-year public and four-year private US colleges to assess the factors that shaped their decision to provide mostly in-person instruction as of August 1, 2020. We consider the roles of the political and religious climate, COVID-19 infections, deaths, and mask mandates, college niche, finances, dormitory capacity, faculty resistance, online readiness, and enrollment pressures. Most notably, we find that decision-making was unrelated to cumulative COVID infection and related mortality rates. The strongest predictor of in-person instruction was the proportion of state residents who voted for Trump in the 2016 presidential election. We also find that dormitory capacity, percentage of revenue from tuition, institutional importance to the local economy, graduation rates, and per capita endowment were associated with providing in-person instruction.
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SciScore for 10.1101/2020.10.15.20213363: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank…
SciScore for 10.1101/2020.10.15.20213363: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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