The case studies in this week’s blog task highlight how racism is built into our educational system, from primary education to higher education and academic careers. Some of the case studies go into analysis of systems of change at play – such as the awarding system of Advance HE, race training modules aimed at staff and students, to interrogate failures within those interventions.
Alice Bradbury’s paper combines policy sociology and Critical Race Theory (CRT) to create a framework for analysing education policy, focusing on racial inequalities. The study uses England’s Baseline Assessment policy as a case study, highlighting its adverse effects on bilingual learners (children with English as an additional language). The assessment, conducted entirely in English, disadvantages these children, establishing low expectations from the start of their education and perpetuating racial inequities. Bradbury argues that policies like these appear neutral but maintain white dominance. The paper illustrates how CRT can reveal the underlying racial biases in education policies and offers a set of questions for a CRT-based policy analysis. This framework helps to critically examine how policies are formulated, their impact on marginalised groups, and the perpetuation of systemic racism within the education system.
Rhianna Garrett’s paper examines how racialised minority PhD students in the UK navigate their academic careers. It highlights the intersectional challenges these students face, including systemic racism and underrepresentation in academia, where professorships are predominantly held by white individuals. Utilising Critical Race Theory and Intersectionality, the study draws on interviews to explore how these students’ identities influence their perceptions and decisions regarding academic careers. The findings emphasise the need for institutions to address structural racism and promote a more inclusive academic environment, going beyond superficial diversity initiatives to foster meaningful cultural change.
She identifies some of these barriers– lack of financial security in academic careers, having one intersectional identity favoured over another in their areas of research, predominantly white spaces creating barriers, lack of role model representation.
In Asif Sadiq’s TED talk he highlights this lack of role model representation that he experiences within his own education. ‘How can I become something I can’t see?’.
He highlights that education gives you one perspective, not all. As teachers, we deliver our lessons in one way to a large group of people with different learning styles, backgrounds, cultural, racial and sexual identities. We assume that everyone that comes into university is equal, but society has created an uneven playing field, which we need to recognise in our student body. We need to address how we teach.
Everyone is an individual with a unique identity rather than representative of groups in which they identify. Could it be that there is an inherent issue with how we analyse the awarding gap?
Our course has an awarding gap in two of the units. We have been working as a team to address how and why this is happening, through staff development sessions on Embedding Conversations on ‘Race’ and ‘anti-racist ideas and practices into our pedagogy and discipline.
We have been exploring the awarding gap through the data sets available on the Moodle. I have been reflecting that the statistics for students do not allow for intersectional analysis, rather they ascribe people to certain groups. Is there a way of exploring this data through an intersectional lens, looking more specifically at students as individuals with a complex range of identities and experiences.
I appreciate this is a large-scale university wide problem, to which this mode of data analysis is useful for mappings patterns across a large volume of people. However, if we are to implement teaching methods which see people not as singular identities but as complex individuals perhaps it makes sense that we use this approach in how we review and analyse the issue.
3 replies on “Blog 3# – Race”
That’s a great comment Lucy around the limitations of data. I have also found myself thinking about how inadequate/superficial our dashboard data is if we really want to address social justice. Just the fact that we only track awarding gaps for home students, for me seems like a huge problem, let alone getting to more granular information about intersectional identities. I am also very weary of the ‘dataification’ of education – as with many other aspects of our society – and would be keen on thinking about other ways we can ‘measure’ student progress and their attainment. Not sure I have any tangible solutions to this yet – but it seems like a question worth asking!
Thank you for your thoughtful comment. I completely agree that our current dashboard data falls short when it comes to addressing social justice issues comprehensively. The focus on awarding gaps for home students alone indeed misses a lot of critical, nuanced information about intersectional identities that could help us better understand and support our diverse student body.
Your concern about the ‘dataification’ of education is very valid. While data can be useful, it often doesn’t capture the full picture of student progress and attainment, especially when it comes to the complexities of individual experiences and identities. Exploring alternative ways to measure and understand student success is essential, even if we don’t have all the answers yet.
Hi Lucy, your insights on systemic racism in education resonate deeply with me. I appreciate your focus on the awarding gap and the need for intersectional analysis, which aligns with my reflections on embedding anti-racist practices in our curriculum. Addressing individual identities in data analysis is crucial for fostering genuine inclusivity. Your point about how policies, while seemingly neutral, maintain systemic inequities, is particularly compelling. It’s essential that we view our students as complex individuals with diverse identities and experiences.