Student vulnerabilities and confidence in learning in the context of the COVID-19 pandemic

ABSTRACT

How did the onset of the COVID-19 pandemic impact student learning in higher education? Everywhere, Sars-CoV-2 struck hardest in the most disadvantaged communities. This paper asks whether the virus's disproportionate effect on more vulnerable groups is replicated among college and university students. Data come from approximately 3800 students studying at nine higher education institutions located in six different countries around the globe. Conventional imagery of the ‘Ivory Tower’ treats colleges and universities as cloistered academic spaces beyond the ‘real world.’ Such imagery suggests that the patterns of COVID-19 inequity seen in the general population might not hold within higher education. However, the composition of the post-secondary student body has become more diverse and more representative. This could mean that patterns of inequity from the general population might hold, although perhaps at muted strength, among college and university students. We investigate the higher education context, asking how the characteristics of students, such as their gender or family background, their digital access, and their living arrangements during the COVID-19 pandemic, impacted their self-reported ability to learn. The paper finds that students in more difficult situations – no study space, too much noise, and poorer health – reported greater disruption to their learning than did their peers who experienced fewer challenging living arrangements. Vulnerability, as measured by students in traditionally marginalized positions, had smaller impacts on student's confidence in learning.

KEYWORDS:

• Student vulnerabilities
• COVID-19
• digital divide
• online learning
• higher education
• teaching and learning

Acknowledgements

The authors are grateful for the support and assistance from a large number of people, including Vincent Alonso, Udeme Anosike, Lisa Chang, Daphne Chalmers, Alex Chow, Catherine Delfosse, Pascal Detroz, Kevin Dullaghan, Hannah Exley, Adam Fein, Timothy Jireh Gaspar, Matthieu Hausman, Cassie Hudson, Françoise Jérôme, Laura Page, Johanna Marion Torres, and Jennifer Vincent. Our thanks to Qiang Fu, Yue Qian, Guy Stecklov, and Carrie Yodanis for comments on an earlier draft of this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The United Kingdom was not alone. Governor Andrew Cuomo of the State of New York tweeted that the rapacious nature of the Sars-CoV-2 virus made it ‘the great equalizer’ (Washington Post, April 5, 2020).

2 ‘Town and Gown’ refers to relations, in university towns like Ann Arbor, USA or Cambridge, England, between the town residents and members of the university (student and faculty gowns).

3 We use several inter-related terms for these student groups – underserved, more marginalized, non-traditional, higher-risk, and more vulnerable. Operationally, we are referring to the groups enumerated in this sentence.

4 Many of our partner institutions introduced new emergency support services, including financial loans/grants and enhanced virtual counseling services. These initiatives attempted to bridge some of the divide in inequality between students, however, these supports likely had less capacity to resolve direct issues around learning, our key research question.

5 Our analytic sample includes only students in courses that transitioned to remote instruction.

6 We include women in this grouping for several reasons. Traditionally women have been underrepresented in higher education, and at least in some fields of study, remain so. Furthermore, women continue to suffer various forms of inequality (Evans 2016; Ridgeway 2011).

7 Cronbach's alpha varies by institution from a low of .61 to a high of .81 with a weighted average (student numbers equalized among partners) of .731.

8 Student loan status and accessibility measures were not asked at all institutions. Some institutions have affordable tuition and no tradition of student loans. With four institutions where all these measures are available (Model 5), loan status and accessibility are not statistically significant.

9 We dropped student loan status and accessibility measures to maximizes institutional breadth. In regressions not shown here, adding questions for loan status and accessibility, but dropping the number of institutions, we find results similar to those shown in Table 5.

10 We explored whether or not difficult living situations were associated with membership in any non-traditional student groups and we found no systematic differences.

11 Including all the vulnerability measures makes no difference here and for parsimony we incorporate only four measures (i.e. loan status and accessibility, with fewer institutions included, are non-significant).

Additional information

Funding

This work was supported by; Ateneo de Manila University (Philippines) received project funding from the Ateneo University Research Council, an off-cycle COVID-19 Research Grant titled “Lessons for Higher Education from the COVID-19 Transition to Online Teaching and Learning.” Deakin University (Australia) received internal project funding. Eindhoven University of Technology (The Netherlands) received project funding from the 4 TU Centre for Engineering Education (4TU.CEE). Humber College (Canada) received internal project funding. The University of Liege (Belgium) received funding within their regular teaching/research remit. The University of British Columbia (Canada) received funding from an off-cycle Teaching Learning and Enhancement Fund. The University of New South Wales (Australia) received internal project funding. Lastly, the University of North Texas (United States) received internal funding from the UNT NetDragon Digital Research Center in the Division of Digital Strategy and Innovation (DSI).