How does education reinforce or challenge social inequalities? Explore the relationship between schooling, social class, and upward mobility through a sociological lens.
The National Student Survey is usually read as a scoreboard for teaching quality. This article argues that the NSS is better understood sociologically: not just as a measure of student experience, but as an instrument that shapes institutional behaviour.
The National Student Survey ranks institutions, shapes league tables, and features in marketing materials as evidence of teaching excellence. But satisfaction is not the same as learning, and the social position of the student completing the survey shapes what they report in ways the instrument cannot detect. This article applies a Bourdieusian lens to the NSS — and finds that the data is telling us something rather different from what it is used to claim.
When universities reach for AI detection tools to police academic integrity, they reach for instruments that are neither accurate nor neutral. Research shows that non-native English speakers, neurodivergent students, and those whose natural writing style resembles AI output face disproportionate false accusations. This article applies a moral panic framework to ask what the response to AI in higher education actually reveals — and who it disadvantages.
Job adverts demand communication, leadership, and resilience. But who actually gets credit for them? Drawing on Bourdieu, Puwar, and Rivera, this article argues that soft skills are not recognised neutrally — they are filtered through class, race, and cultural capital. The result is a hiring system that mistakes social advantage for individual merit.
Widening participation policy is often judged through dashboards of access, continuation and attainment. Yet focusing on who gets in – and who stays – can mask how universities continue to privilege particular histories, dispositions and futures. Drawing on Bourdieu’s concepts of habitus, capital and institutional habitus, this article argues that belonging should sit at the centre of how we interpret student data, and explores what a more “belonging-sensitive” approach to WP metrics might look like in UK higher education.
Student recruitment dashboards promise a single version of the truth about who will enrol. This article shows how small choices about funnels, conversion and melt can create competing “truths”, quietly shape who gets attention, and reproduce inequality in HE – and suggests practical ways to use dashboards, AI and KPIs more reflexively.