Conditional Belonging: What Minority Ethnic STEM Students Tell UK Universities

By Student Voice AI

Published Feb 14, 2026 · Updated Feb 14, 2026

At Student Voice AI, we see universities invest heavily in “belonging” initiatives — but student voice data often shows that belonging is not evenly available. A recent open-access paper in Higher Education by Chiu, Wong, Murray, Horsburgh and Copsey-Blake explores this through the concept of conditional belonging for minority ethnic STEM students in UK higher education. We’ll summarise what the study found, and why it matters for teams using student feedback to improve inclusion and engagement. [Paper Source]

Context and research question

Universities commonly frame belonging as something you can promote through representation, messaging, and student experience programming. But for many students from underrepresented backgrounds, belonging is experienced less as a stable “feeling at home” and more as an ongoing negotiation: when do I feel accepted, and under what conditions?

Chiu et al. ask how minority ethnic students experience and construct belonging — and how that belonging can be “conditional” (dependent on context) and “conditioned” (shaped by prior experiences and institutional norms). The study is part of a two-year qualitative project. The wider dataset includes semi-structured interviews with 110 STEM students (conducted online between June and December 2020). This paper analyses 72 interviews with minority ethnic students across two pre-1992 English universities described as having international reputations and “elite” status, using a social constructionist approach and iterative coding in NVivo.

Key findings

The core contribution is conceptual: belonging is not a yes/no state. For these students, it can be contingent on performance, on who is in the room, and on the perceived risk of being read through stereotypes.

First, the authors describe how institutional elitism and competitiveness can make belonging feel earned rather than granted. When students perceive that they must continuously prove they “deserve” their place, they are more likely to interpret setbacks, confusion, or normal academic struggle as evidence of not fitting in — which can narrow participation and reduce help-seeking.

Second, students’ accounts show how ethnicity shapes academic belonging through everyday interactions. Belonging in seminars, labs and group work can be undermined by being one of the only minority ethnic students in a space, experiencing exclusionary behaviour, or feeling pressure to represent a whole group. The result is often heightened vigilance: students assess whether a space is “safe enough” to ask questions, make mistakes, or contribute.

As the authors put it:

"students’ construction and negotiation of belonging can be ‘conditional’ and ‘conditioned’"

Third, the paper highlights tensions in social belonging. Students navigate a familiar double bind: seeking “safe” relationships with people who share experiences can be protective, while also being misread as self-segregation. Belonging is shaped not only by formal teaching, but by who gets included in informal networks — and by whether campus social spaces, norms, and events feel welcoming in practice.

Across themes, the practical point is consistent: conditional belonging changes how students participate. It affects confidence, willingness to speak, who takes leadership in group work, and whether students interpret institutional support as “for people like me”.

Practical implications

For UK HE teams, the paper points to interventions that are less about slogans and more about daily design:

Treat transition points as belonging-critical moments. Early-stage experiences can lock in assumptions about who “belongs” in a programme or institution. Design induction and early assessment as confidence-building, not sorting mechanisms.
Make academic spaces actively inclusive. Train staff to recognise and respond to exclusionary dynamics (including microaggressions), and embed anti-racist practice in teaching, assessment, and group work design so students can participate without self-censoring.
Build safe routes to seek help and report issues. If belonging is conditional, students may avoid help-seeking when they fear being judged. Clear support pathways, tutor check-ins, and trusted reporting processes for exclusionary behaviour can reduce that risk.
Design social inclusion, not just social opportunity. Inclusive social spaces require practical choices (who is centred, how events are structured, what “normal” looks like) — not only more events. Induction activities and campus events should signal inclusion in the details, not only in messaging.
Use student voice data to detect conditional belonging at scale. Ask open-text questions that invite students to describe when they feel able to participate, who they can be honest with, and what makes a space feel unsafe. Segment findings by student characteristics and close the loop with visible action.

Student Voice Analytics supports this by categorising belonging and inclusion signals in comments (alongside related themes like assessment fairness, teaching behaviours, and peer dynamics) and benchmarking how experiences differ by cohort and demographic.

FAQ

Q: How can universities identify “conditional belonging” in student feedback?

A: Look for patterns in when and where students feel comfortable participating, not only whether they report “belonging” in general. Open-text prompts such as “When do you hold back in class?” or “What makes group work feel safe or unsafe?” tend to surface the conditions students are responding to. Analysing those comments by cohort and demographic can reveal whether belonging is stable or contingent for particular groups.

Q: What are the limits of this study’s method for understanding belonging?

A: The study uses qualitative interviews, which are well-suited to understanding lived experience and meaning-making, but they do not estimate prevalence in the way a survey would. The context also matters: interviews were conducted online during 2020, and the institutions are described as elite, which may shape how competitiveness and status are experienced. For practice, the implication is to triangulate: use interviews and focus groups for depth, and student voice survey comments for breadth and monitoring over time.

Q: What does “conditional belonging” change about how we interpret student voice metrics?

A: It suggests that averages can be misleading. A programme can look “fine” on high-level satisfaction while specific groups are navigating extra friction: avoiding certain spaces, self-censoring, or disengaging from peer networks. Free-text comments are often where this becomes visible, because students describe concrete situations (who spoke, what was said, what was assumed) that don’t translate into a single scale point.

References

[Paper Source]: Yuan-Li Tiffany Chiu, Billy Wong, Órla Meadhbh Murray, Jo Horsburgh, Meggie Copsey-Blake "‘I deserve to be here’: minority ethnic students and their conditional belonging in UK higher education" DOI: 10.1007/s10734-025-01469-1

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