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  5. Analysis of COVID-19’s impact on BAME students’ attainment (A case study of Level 1 C&C Open University modules)

Analysis of COVID-19’s impact on BAME students’ attainment (A case study of Level 1 C&C Open University modules)

Project leader(s): 
Dhouha Kbaier and Soraya Kouadri Mostefaoui
Theme: 
Faculty: 
STEM
Status: 
Current

A range of evidence from new data sources indicates that historically marginalised sections of the population, namely those from Black, Asian, and Minority Ethnic (BAME*) backgrounds, suffer disproportionally from the impacts of the COVID-19 [1]. For instance, a study by the Intensive Care National Audit and Research Centre revealed that 35% of patients infected by the virus were non-white, which is nearly triple the 13% proportion in the UK population as a whole (https://www.theguardian.com/world/2020/apr/07/bame-groups-hit-harder-covid-19-than-white-people-uk). BAME students, as part of this disadvantaged community, are particularly vulnerable to the fallout of coronavirus. One of the major issues facing all universities prior to Covid-19 was the scandalous BAME degree awarding gap, and it is likely to be an even bigger issue now. The project aims to investigate the impact of COVID-19 on BAME students’ attainment at the OU by means of a combination of qualitative and qualitative data analytics.

Previous work at The OU [2] on traces of 150,000 students confirms the existence of an attainment gap of BAME students, who are at least 20% less likely to achieve excellent grades. More importantly BAME students spent 4-12% more of study time to achieve the same academic performance as white students.

This project aims to first understand patterns of BAME students’ progression and retention by conducting large-scale data analytics in the core level 1 modules namely, TM111/TM112, as well as to assess the impact of COVID-19 on the BAME students’ attainment and study experiences. 

As argued in many research, data-driven, student-cantered approaches can reduce attainment gaps in higher education [3, 4]. Therefore, we will use the findings of these analysis to drive focus groups and interviews with students and teaching staff.


[1] Mamluk L, Jones T. The impact of COVID-19 on black, Asian and minority ethnic communities. National Institute for Health Research (NHR) report. 20/05/2020.

[2] Nguyen Q., Rienties B. Richardson J.T.E. (2020) Learning analytics to uncover inequality in behavioural engagement and academic attainment in a distance learning setting, Assessment & Evaluation in Higher Education, 45:4, 594-606, DOI: 10.1080/02602938.2019.1679088.

[3] Panesar, L., 2017. Academic support and the BAME attainment gap: using data to challenge assumptions. Spark: UAL Creative Teaching and Learning Journal, 2(1), pp.45-49.

[4] Liu, D. Y.-T., Bartimote-Aufflick, K., Pardo, A., & Bridgeman, A. J. (2017). Data-Driven Personalization of Student Learning Support in Higher Education Learning Analytics: Fundaments, Applications, and Trends (pp. 143--169): Springer.

* This information is drawn from self-designations of ethnicity on enrolment forms. The acronym BAME may not be a preference of all students designated as BAME by the institution (https://www.bbc.co.uk/news/uk-53194376)

Dhouha Kbaier and Soraya Kouadri Mostéfaoui poster

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