Abstract
This article presents an innovative application of Q methodology to address challenges of diversity, inclusion, and belonging within Management Education. Using a three-phase mixed method research design (n = 123), the study combines focus groups, Q sorting, and follow-up interpretation to explore how students and employers conceptualise academic and professional success and their relationship to belonging. Participants included undergraduate students studying in the United Kingdom (n = 96) alongside employer representatives involved in graduate recruitment (n = 27). The analysis identifies distinct sensemaking patterns and subjective narratives that shape perceptions of academic and professional success and belonging. By examining intersections of demographic characteristics, including gender and UK versus international student status, in relation to Q sorting patterns, the findings show that student perspectives often diverge from conventional demographic categories. Instead, this study captures the complexity of belonging, offering bottom-up insights into cognitive differences at a granular level, thus laying a foundation for fostering inclusive academic environments. This approach not only identifies the potential of cultures of belonging but also offers a pathway for helping to establish them, showing how shared goals can emerge despite diverse backgrounds. The study also advances methodological discourse by suggesting adaptations to traditional Q methodology, making it more accessible to diverse research communities.
Introduction
Students’ sense of belonging continues to present a pressing challenge for Higher Education (HE) (Ajjawi et al., 2023; Crawford et al., 2024; Haddow & Brodie, 2023). It impacts student retention and satisfaction worldwide and particularly affects non-traditional learners (Crawford et al., 2024). Addressing this situation calls for innovative approaches (Haddow & Brodie, 2023) capable of emphasising the personalised nature of belonging. Such approaches should allow for critical dialogues between staff and students to explore diverse avenues through which students might feel that they belong (Ajjawi et al., 2023).
This paper discusses Q methodology's potential as a tool to tackle belonging challenges in HE at a time of ‘diversity fatigue’ (Smith et al., 2021). Q methodology is a research approach designed to systematically explore subjectivity by asking participants to rank statements according to their personal viewpoints, with factor analysis used to identify shared patterns of perspective (Brown et al., 2015; Ramlo, 2016; Watts & Stenner, 2012). We use Q methodology as a vehicle for cultivating a sense of belonging which helps students and staff to share an inclusive academic culture. By doing so we make a novel methodological intervention into the diversity and inclusion debate. We intend the knowledge gained via this approach to contribute to the identification and removal of exclusionary practices within HE (e.g., how to reduce the degree awarding gaps), and to promote the recognition and inclusion of diversity.
For the most part research on belonging is dominated by positivistic and post-positivistic approaches which strive to measure belonginess and correlate it with other variables presumed objective (such as demographic characteristics). A considerable challenge arises from the need to reconcile divergent perspectives on a given phenomenon. The task of reconciling the ‘objective’ approach, which seeks to provide a neutral external evaluation, and the ‘subjective’ approach, which embodies the insider's experiential viewpoint, a complex matter for educators, researchers, and scholars alike.
A common starting point is to treat categories like gender, sexuality, ethnicity, disability, class, age, nationality, and ‘native speakerism’ (Holliday, 2006) as variables, understood to determine unequal outcomes either singly or conjointly. Policymakers, practitioners, and students alike want to know ‘facts’ about how these variables impact outcomes, so that they can introduce measures to eliminate unjustifiable disadvantages. On the other hand, there is a tradition of research which recognises that these categories have irreducibly subjective aspects that escape objectively applied categories. Rather than treating demographic identity as a fixed explanatory variable, our approach foregrounds the subjective and relational processes through which students construct belonging, enabling analysis of both shared and divergent narratives within diverse groups (Cikara et al., 2022).
Connecting Q methodological research to the growing debates around intersectionality of demographic characteristics, gives attention to the always conjoint operation of multiple categories, and to the mixture and entanglement of objective conditions and experience. A sense of belonging can be facilitated if attention is given both to a) the differences of those involved in the issue at play (i.e., the polyphony of multiple perspectives which may or may not correspond to demographic variables) and b) to areas of consensus where there is like-mindedness despite diversity. Because it gives ‘bottom up’ access to differences and commonalities of viewpoint at a granular level, Q methodology allows attention to be given to both.
We conducted our research as a three-phase mixed-methods study: First we use semi-structured questionnaires to understand the context from the perspective of the students experiencing the phenomenon. We then use Q methodology to derive and compare sense-making patterns in a ‘bottom-up’ manner based on the Q sorting activity of participants. By ‘bottom up’ we mean that the resulting ‘taxonomy’ of viewpoints is the effect of the activity of the participants themselves. An examination of the resulting ‘bottom up’ taxonomy reveals emergent patterns that do not map onto ‘top down’ categories (like gender or home, i.e., domiciled in the United Kingdom (UK), versus international student status) in any simple way. Similar to Bhatti et al. (2022), to gain multiple perspectives, our research focuses in this phase on business students in their final year of undergraduate studies at a UK university, and industry professionals, representing the students’ future employers and colleagues. In the third phase we unpack the findings across five student focus group discussions. Appendix 1 outlines the number of participants per phase.
The substantive issue for discussion across the three phases was about students’ perception of the factors which will impact their academic and their professional success in their final year of their undergraduate studies. We answer the following research questions (RQs): RQ1: What do students and employers attribute as factors influencing their academic and professional success? RQ2: Does demographic group belonging shape the attribution of factors influencing their academic and professional success? RQ3: How can our research findings help establish belonging in ways that do not just
Before unpacking our methodology and findings for each of the three phases, we will first provide a brief overview of the core theoretical matters of diversity challenges, principles of belonging, and the role of storytelling, while noting that Q methodology offers interpretive insight rather than generalisable claims.
Diversity Challenges, Belonging, and Storytelling
Diversity challenges in education are complex and encompass multiple dimensions, from the demographic dimension through the experiential dimension to the cognitive dimension (de Anca & Aragón, 2018). Developing belonging is increasingly seen as a fundamental goal for addressing outcome disparities between students from demographically diverse backgrounds (UUK-NUS, 2019). Korpershoek et al. (2020), for example, found links between a sense of belonging and outcomes like goal orientation, social-emotional satisfaction, and self-efficacy.
Belonging is a multi-scalar concept (Almarode et al., 2024, 2025), and there is no single definition or measure of belongingness within educational psychology generally (Allen et al., 2021a, 2022; Mahar et al., 2013). While belonging can be seen as a fundamental psychological need, it is also context dependent. For instance, belonging to a particular group, such as a cohort or institution, is often influenced by specific circumstances and factors (Allen et al., 2021a).
To feel a sense of belonging, several processes need to converge for the group member, including competencies, opportunities, motivations, and perceptions (Allen et al., 2021a), but there must also be recognition and acceptance by the collective. This makes belonging both subjective and self-determining, and yet dynamically related to objective and intersubjective factors (Mahar et al., 2013). Belonging must involve a relation between a ‘member’ (who perceives themselves to belong) and a perceived unity (a club, a family, a school, a nation) to which they belong to some degree. Hence, ‘belonging’ presupposes the variable of some actual history of involvement of a member with a broader unity, and it is in this context that notions like the ‘established’, the ‘outsider’ and the ‘excluded’ acquire particular relevance.
Recent research highlights that belonging in HE is increasingly shaped by digital learning environments. Studies of online and hybrid education suggest that feelings of connection, recognition, and participation can emerge through virtual interactions, although these forms of belonging are often more fragile and dependent on intentional pedagogical design (Bond & Bergdahl, 2023; Kahu et al., 2020).
Martin (2015) and Rezvani and Gordon (2021) associate belonging with the achievement of greater understanding of peers through storytelling practices that allow the storyteller to feel part of the story of the wider collective. This allows members of a community to understand that their values are aligned with others of their community, fostering in return higher levels of cognitive flexibility and creativity (Kundro, 2023). But, of course, this storytelling cannot be a monologic affair. To be recognised and to recognise oneself as belonging, a person's stories must weave together with those of others, each story should be to some degree unique and different, and to some degree common and shared.
Finally, previous belonging research in higher education has primarily relied on large-scale surveys or qualitative interviews that capture perceptions of inclusion but not the relational structure of those perceptions. While such approaches indicate broad trends, they often flatten individual nuance and reinforce demographic categories rather than exploring how students’ sense-making processes cut across them. This research applies Q methodology as a sense-making framework that shows the subjective architectures of belonging. This approach moves beyond traditional attitudinal analysis by enabling participants to actively construct and compare their own narratives of inclusion, thereby exposing the tensions between meritocratic ideals, institutional expectations, and personal identity work.
The interpretive and reflexive orientation of this paper informs the methodological design presented below and frames our contribution as both analytical and dialogical, seeking not only to understand belonging but also to support its cultivation within higher education. To explore these layered experiences of belonging, and to show how students construct meaning around inclusion, the study employed Q methodology. The following section outlines the design, participant sample, and analytic procedures that guided this interpretive approach.
Methodology
This section outlines the methodological framework used to investigate subjective perspectives on academic and professional success and their relationship to belonging. The study employed Q methodology within a three-phase research design. Phase 1 generated the concourse of statements through exploratory qualitative data collection. Phase 2 conducted the Q sorting study with students and employers. Phase 3 used focus group discussions to interpret the emerging viewpoints. Each phase is described below together with its participants and analytical procedures.
Introduction to Q Methodology
Q methodology was first proposed by William Stephenson in 1935 and is used to examine subjective viewpoints on a given topic (Brown et al., 2015; Ramlo, 2016; Watts & Stenner, 2012). Participants are invited to rank a shared set of statements according to their personal perspective, allowing patterns of similarity and difference between viewpoints to be identified. Originally developed within psychology, the method has since been applied across a wide range of fields including political science, environmental research, policy studies, and health research (Davis et al., 2014).
A typical Q study involves four stages. First, a concourse of statements representing the discourse around a topic is generated and refined into a Q set. Second, participants rank these statements according to their level of agreement or disagreement, producing individual Q sorts. Third, the completed Q sorts are correlated and subjected to by person factor analysis. Finally, the resulting factors are interpreted to explain clusters of shared viewpoints. For example, Stickl Haugen et al. (2019) developed a Q set of 39 statements relating to student belonging and collected Q sorts from 43 middle school students. Factor analysis resulted in three distinct viewpoints which were interpreted as different understandings of belonging within the school environment. Each factor represented a shared pattern of meaning among participants who ranked the statements in similar ways.
Q methodology combines quantitative and qualitative elements. The ranking of statements allows for statistical identification of viewpoint patterns, while interpretation focuses on the qualitative meaning of these patterns. Unlike conventional survey research, Q methodology does not aim to generalise findings to a population and therefore does not require a statistical power analysis in the conventional sense. Instead, it seeks to identify the range and structure of viewpoints that exist within a given context. For this reason, sample sizes are typically modest, often between forty and sixty participants (Watts & Stenner, 2012). However, online data collection has enabled larger Q studies in recent years (Davis et al., 2014; Nynäs et al., 2022; Song & Ko, 2017).
A key feature of Q methodology is that the resulting classifications of viewpoints emerge from the sorting patterns of participants rather than being imposed by researchers. This bottom-up approach allows subjective perspectives to be explored without assuming that they align with predefined demographic or institutional categories.
Study Design
The research was conducted in the UK between 2018 and 2021 and consisted of three phases that sequentially informed one another.
Phase 1 – Concourse Development
The first phase generated the concourse of statements used in the Q sorting study. Ten management students from diverse demographic backgrounds completed semi structured questionnaires describing perceived enablers and obstacles to academic and professional success. Their responses were analysed qualitatively and formed the basis of the statement pool used to construct the Q set (see Appendix 2 for the questionnaire and sample responses).
Phase 2 – Q Methodology Study
The second phase involved the Q methodology study itself. A Q set of 45 statements derived from the Phase 1 concourse was developed to capture factors perceived as relevant to academic and future professional success. Eighty-two participants completed Q sorts. These participants included 55 final year undergraduate students and 27 employers who were involved in graduate recruitment and early career hiring. Each participant ranked the 45 statements according to their perceived importance for academic and professional success. The completed Q sorts were then correlated and analysed using by person factor analysis. This analysis identified clusters of participants who ranked the statements in similar ways, elucidating distinct cognitive configurations or viewpoints.
Phase 3 – Focus Group Interpretation
The third phase used focus group discussions to interpret the findings of the Q analysis. Five focus groups involving a total of 31 students were conducted. Participants reviewed the preliminary factor interpretations derived from the Q study and discussed their meaning and implications for academic success and belonging (see Appendices 3 and 4). Discussion prompts used during the sessions are provided in Appendix 5. These discussions enriched the interpretation of the factors and helped contextualise the viewpoints identified in the Q analysis. Across the three phases of the primary study, 123 individuals participated.
A post-hoc replication of the study, including focus groups, with an additional research ethics approval, was later conducted at a second UK business school and produced comparable findings. This replication is referenced in the discussion but is not included in the participant count reported here.
Materials and Technology
Data collection for the Q sorting study was conducted online using QsorTouch, a software platform approved by the focal business school. For the post-hoc replication study, Qualtrics was used due to institutional requirements at the second university. Data were exported as CSV files, consolidated, and stored in Excel. The Q methodological analysis was conducted using Zabala's (2016) open access Q method package in R, implemented through RStudio. Once installed, the analysis scripts allow efficient processing of Q sorts and factor extraction.
Participants and Sampling
Across the three phases of the study, 123 individuals participated. This included 96 undergraduate business school students and 27 employers and industry professionals. Students were drawn from final year undergraduate programmes at a research-intensive UK university, while employer participants represented sectors relevant to graduate career pathways.
Participants were recruited through departmental announcements and professional networks following institutional research ethics approval. Participation was voluntary and informed consent was obtained from all contributors prior to data collection. Participants in the Q sorting phase provided written consent before completing the sorting task, while focus group participants confirmed written consent before the discussion commenced. The participant pool reflected the demographic profile typical of UK business schools, with a balance of gender and a larger proportion of international than home students. Black home students were underrepresented, and we expand on this limitation in the limitations’ section.
Table 1 contextualises the participant pool by displaying the demographic distribution of participants across gender and home/international status for students and gender and number of staff for the employers. Appendix 1 shows the detailed number of demographics per research segment (Concourse, Q methodology study, Focus group discussions).
Participant Student Demographics by Gender and Home (UK-Domiciled) Versus International status and Employer Demographics by Gender and Number of Staff.
Researcher Positionality and Reflexivity
As researchers, we acknowledge that our positionalities shaped both the design and interpretation of this study. The project team comprised a management educator with responsibility for equality, diversity and inclusion strategy, and a social psychologist specialising in Q methodology. This combination offered disciplinary breadth and reflexive awareness of institutional power relations.
Belonging research necessarily involves asymmetries between staff and students. We therefore engaged in continuous reflexive discussion throughout data collection and analysis, examining how our assumptions might influence statement framing, participant interpretation, and factor labelling. Following Braun and Clarke (2022) and Pillow (2003), we regard reflexivity as an ongoing process rather than a methodological stage, recognising that interpretive knowledge is co-produced between researchers and participants.
Results
The results are organised in three stages reflecting the sequential design of the study. First, we report the Q methodology findings, including the development of the concourse and the factor structure that emerged from participants’ sorting activity. Second, we present the focus group findings, which provide interpretive depth on the cognitive and emotional dimensions associated with these factors. Third, we outline the seven factor interpretations, each representing a shared viewpoint on academic and professional success and experiences of belonging. Together, these stages illustrate how participants prioritised different enablers and obstacles to success, and how demographic identities did not deterministically relate to the cognitive orientations shaping these viewpoints.
Q Methodology Results
Concourse Development
The Q sort items responding to RQ1 were generated by ten students through semi structured questionnaires (see Appendix 2 for the questionnaire and a sample response). Participants were asked to reflect on their final year of study and identify perceived enablers and obstacles to academic and professional success. This process generated an initial pool of 98 statements. After removing duplicates and clarifying ambiguous wording, the list was reduced to a Q set of 45 items. These statements formed the basis of the Q sorting exercise and were randomly numbered for presentation to participants. The full set of items is presented in Appendix 3.
Q Sorting Study and Factor Extraction
Participants completed the Q sorting exercise online by ranking the 45 statements along a quasi-normal nine-point distribution ranging from +4 (most strongly agree) to −4 (least agree). Prior to sorting, participants categorised statements into three preliminary groups of agree, neutral, and disagree before placing them on the final distribution grid. Eighty-two Q sorts were collected from 55 final year undergraduate students and 27 employers involved in graduate recruitment. Participants also provided optional demographic information, including gender and nationality.
Each completed Q sort was correlated with all others before the resulting matrix was subjected to by person factor analysis using the Q method web package in R (Zabala, 2016). Pearson correlations were calculated, and principal component analysis followed by Varimax rotation was applied to identify clusters of similar sorting patterns. Several approaches were considered when determining the number of factors to retain, including the Kaiser Guttman criterion and scree test. The final analysis followed the “magic number seven” approach proposed in early Q methodology work (Brown, 1980 cited in Watts & Stenner, 2012), which corresponded closely with the point at which eigenvalues levelled off in the scree plot.
The resulting seven factor solution accounted for 55 per cent of the total study variance, a level considered acceptable in Q methodological analysis (Watts & Stenner, 2012). For each factor the software generated a composite Q sort representing the shared ranking pattern among participants loading significantly on that factor (see Appendix 3). Factor interpretation is based on the composite Q sorts and the set of significantly loading participant Q sorts identified by the analysis software (see Appendix 4). Table 2 summarises the number of participants and variance explained by each factor.
Summary Number of Participants and Variance per Factor.
Patterns Emerging from the Q Study
Factor 1 represented the viewpoint of more than half of the student participants and explained over 20 per cent of the variance. Across the remaining factors, the analysis indicated multiple distinct configurations of attitudes toward academic and professional success. Comparing student and employer perspectives showed notable differences in priorities. Students placed greater emphasis on attendance, ambition, and analytical skills. Employers placed greater emphasis on teamwork, verbal communication, confidence, and the role of luck.
When focusing only on students, the factor structure did not align with conventional demographic categories such as gender or home versus international student status (see Appendix 4). Instead, participants across different demographic backgrounds were distributed across multiple factors. Table 3 summarises how participants mapped onto the seven factors according to gender and home or international status.
Demographic Distribution of Participants Across the Seven Factors.
Of the student participants, 45 loaded significantly on one of the seven factors. Approximately 18 per cent of students (n = 10) did not load strongly on any factor. These non-loading cases suggest that while several shared viewpoints were identifiable, some participants expressed more individually nuanced perspectives that did not align strongly with the dominant attitudinal patterns.
Across the factors, no single demographic group dominated any viewpoint. Each factor included a mixture of gender identities and student backgrounds. This pattern supports the broader argument that demographic characteristics alone do not deterministically shape the cognitive orientations reflected in participants’ sorting decisions.
Focus Group Discussions
In the final third phase we complemented the Q methodology study and conducted five in-depth focus group discussions with students (see Appendix 1 for the number of participants per demographic segment). In the focus group discussions, we explored several key areas related to students’ reflections on their studies in preparation and as support for achieving academic and professional success. We also shared the results of the Q methodology study (Appendices 3 and 4). Appendix 5 shows the guiding questions for the focus group discussions.
In each of the focus group discussions, the tension between individuality and conformity was a central theme. Students were initially keen to explain their individuality, highlighting the importance of recognising and valuing diverse identities within the academic environment. One home student shared, ‘I did not feel like I was acknowledged as a black woman… it felt as if my presence did not matter.’ Another openly queer student noted that while there is no overt discrimination, there is a lack of awareness ‘There's no discrimination, but there does not seem [sic] awareness either, it's ignored.’ This ignorance felt for participants like a lack of support, especially when combined with strong implicit expectations of conformity which leads to students ‘second guessing their own behaviour and self-expression.’
An international student pointed out the difference between international and home students. For example, one student mentioned, ‘International students hate it when lectures say “everything looks good”. English culture is all positive, but you don’t mean it.’ Another student added ‘I think it's the culture. Asians are afraid of speaking [in class]. We are afraid that you are talking about A but we are talking about B.’
Independent of home or international student status, students commented on a perceived ‘need to fit in’. This sentiment was captured in the statement, ‘The issue are the barriers that keep students from allowing themselves to be themselves,’ leading to the student-developed question, ‘Can I be who I am, and am I appreciated for my uniqueness?’ Such concerns reflect the internal conflict students face between maintaining their individuality and conforming to perceived norms. Focus group participants suggested celebrating diversity more openly so that students can fully express themselves and be appreciated for their uniqueness.
When discussing the Q methodology results with students, focus group participants suggested communicating more openly the findings linked to the demographic differences and their intersectionality to counteract the perception of trying not to notice differences in a quest for equality. Students voiced that more explicit talk about cognitive diversity and similarities might help them develop a sense of belonging to a community where they can dare to be themselves rather than strive towards conformity. Reviewing the results they noted that there were similarities they were unaware of previously: ‘I think perhaps people's perception of others is wrong.’
Q methodology results thus allowed us within the focus group discussions to move towards integration and connections of students and ideas to create synergies. Students suggested personalised and tailored internal communication as well as initiatives that encourage engagement between student groups to achieve a greater understanding of peers, pointing out to students that for some aspects they are appreciated for their uniqueness and that for others they are attitudinally like-minded, also when demographically diverse.
These reflections helped contextualise the statistical patterns identified in the Q methodology analysis. While the factor analysis outlined clusters of shared viewpoints regarding academic and professional success, the focus group discussions explained how students interpreted these orientations within their lived educational experience. In particular, the discussions highlighted tensions between individuality, conformity, and recognition within the university environment, themes that resonate across several of the extracted factors. The seven factors presented below therefore represent not simply statistical groupings of Q sorts, but coherent viewpoints that articulate different ways of understanding success, belonging, and agency within management education.
Interpretation of the Seven Factors
Building on the focus group discussions, we developed interpretive narratives for the seven factors identified in the Q methodology analysis. Each factor represents a distinct viewpoint on how academic and professional success, inclusion, and belonging are understood within higher education and early career contexts. The factors range from strongly agentic orientations emphasising planning and ambition to perspectives shaped by structural constraint and uncertainty.
As noted in Table 3, nearly 20 per cent of students did not load significantly on any factor. This indicates that divergence exists not only between the seven dominant viewpoints but also in more individualised ways of interpreting success and belonging that are not easily captured by demographic categories. This reinforces the value of Q methodology for identifying subtle patterns of subjectivity beyond conventional demographic framings.
Factor 1: the Strategic Achiever – Belonging Through Structured Performance
This viewpoint emphasised planning, organisation, and disciplined self-regulation. High loading statements highlighted the importance of time management and preparation, while statements externalising failure were strongly rejected. For these participants, belonging was experienced as an outcome of demonstrating competence rather than through relational connection.
The emphasis on planning functioned as a strategy for managing uncertainty within what students perceived as a highly evaluative environment. Focus group discussions reinforced this pattern, with several students describing a desire to appear reliable and conforming rather than experimental. This aligns with research suggesting that belonging in competitive academic contexts can become tied to visible productivity and performance (Allen et al., 2021b). In this factor, belonging therefore appeared conditional on sustained demonstration of competence.
Factor 2: the Ambitious Performer – Achievement Despite Stress
Participants associated belonging with ambition and recognition. Stress and pressure were interpreted as indicators of commitment, and high academic aspiration was framed as a desirable attribute. Statements emphasising ambition and academic achievement loaded strongly. Within this viewpoint, emotional strain became normalised as part of demonstrating dedication. Students described pressure both as a burden and as a signal of seriousness. This pattern reflects research on the moralisation of work in high performance settings, where perseverance through stress is interpreted as evidence of virtue (Kundro, 2023). Belonging therefore emerged through visible striving and sustained forward momentum.
Factor 3: the Autonomous Learner – Independence as Self-Protection
Participants loading on this factor defined belonging through autonomy and intellectual self-confidence rather than social affiliation. Many expressed a preference for working independently and viewed group work as a potential threat to their academic performance. Autonomy functioned both as a cognitive preference and as an emotional safeguard. By working alone, participants felt able to preserve control over their academic identity and reduce exposure to judgement. Consistent with literature on academic self-efficacy (for example Korpershoek et al., 2020), independence allowed students to maintain confidence and minimise perceived risks associated with collaborative work. Belonging for this group was therefore primarily epistemic rather than social.
Factor 4: the Analytical Thinker – Cognitive Engagement Over Social Participation
This factor reflected a strong orientation toward intellectual engagement. Participants valued critical thinking and described belonging as emerging through shared interest in ideas rather than through social interaction. Students associated inclusion with opportunities to analyse, debate, and explore concepts in depth. Focus group discussions indicated that some felt marginalised within socially oriented university cultures but comfortable in intellectually focused settings. This pattern resembles what Mahar et al. (2013) describe as cognitive belonging, where inclusion is experienced through shared reasoning rather than shared identity. Belonging therefore arose through engagement with the curriculum itself.
Factor 5: the Pragmatic Insider – Confidence in Systems and Fairness
Participants expressing this viewpoint demonstrated strong trust in institutional fairness and meritocratic processes. They believed that effort would lead to success provided the rules were applied consistently. Demographic characteristics were generally viewed as irrelevant to outcomes. This perspective aligns with meritocratic narratives often associated with institutional insiders who perceive organisational systems as predictable and fair (Bourdieu, 1977; 1990). Several employers mapped onto this factor, reinforcing its institutional orientation. However, this viewpoint contrasted with perspectives expressed elsewhere in the study that highlighted structural barriers. The factor therefore shows how assumptions about fairness can coexist with experiences of inequality among other participants.
Factor 6: the Constrained Achiever – Financial Precarity and Perceived Exclusion
Participants in this group shared the ambition evident in earlier factors but emphasised financial constraints and competing responsibilities. Many described working alongside their studies to maintain financial stability, which created pressure and exhaustion. Despite strong commitment to academic success, these students often felt overlooked or disadvantaged because they lacked access to influential networks. Their experiences resonate with research on the hidden curriculum, where implicit expectations privilege those with greater cultural and financial resources (Koutsouris et al., 2021; Martin & Byrd, 2025). Belonging was therefore shaped by a continuous negotiation between aspiration and material constraint.
Factor 7: the Fatalistic Realist – Success as Circumstantial Rather Than Earned
This viewpoint questioned the link between effort and outcome. Participants frequently attributed success to luck, timing, or external circumstances rather than individual performance. Such external attribution patterns are commonly associated with contexts where institutional processes appear opaque or unpredictable (Reay, 2018; Reay et al., 2005). Focus group reflections suggested that observing inconsistencies between effort and reward contributed to this perception. While this perspective may function as a psychological buffer against disappointment, it also reduced engagement by weakening belief in institutional fairness. Belonging therefore appeared fragile and contingent.
Figure 1 summarises the divergent orientations underpinning belonging across the seven factors. Each factor aligns with a distinct combination of personal disposition, structural condition, and theoretical lens, highlighting the multiplicity of belonging logics within higher education.
Divergent orientations of belonging across the seven factors.
Across all seven factors, belonging emerged as a negotiated and dynamic process rather than a static state. Participants articulated belonging through differing logics of effort, recognition, and institutional trust, with each factor emphasising routes through which individuals sought legitimacy and coherence within higher education. The factor interpretation indicates that how participants thought about success, fairness, and visibility played an important role in shaping their belonging narratives. Taken together, the factors illustrate a landscape in which belonging was continually constructed through interactions between personal disposition, perceived institutional expectations, and the wider social and material conditions that framed academic life. These patterns provide the foundation for a broader examination of the shared values and structural tensions that underpin the experience of belonging across the sample, which will be explored in the following Discussion section.
Together, these seven factors illustrate the diverse cognitive and emotional landscapes through which students experience belonging. The discussion that follows situates these findings within the broader literature on inclusion, identity, and higher education culture.
Discussion
This study examined how students and employers interpret the factors that influence academic and professional success, and how these interpretations shape experiences of belonging in higher education. The findings demonstrate that belonging is not a uniform, static, or predictable condition, but a dynamic and negotiated process shaped by differences in agency, structural constraint, emotional labour, and access to resources. The analysis of the seven factors provides a rich account of these variations and illustrates how divergent logics of belonging coexist within the same institutional environment.
The Discussion is organised into four parts. The first part situates the findings within broader conceptual work on constructs, identity, and intersectionality. The second part examines the importance of accounting for divergence, drawing on the factor analysis and associated literature. The third part considers the methodological and the fourth part outlines the practical implications of the research.
Construct Specificity, Intersectionality, and the Cognitive Foundations of Belonging
Constructs can be operationalised at different levels of specificity and sit along a hierarchical spectrum (de Vellis, 1991). In this study, three levels of specificity were central to understanding students’ perceptions of the factors shaping success and belonging.
At the first level, students identified enablers and obstacles to academic and professional success. Planning and time management were ranked as most important by a majority of participants, mirroring the findings of Sutherland et al. (2018). While that study linked the impact of organisation on student satisfaction to institutional systems, our results suggest that students viewed institutional organisation as a precondition for their own ability to be organised.
The second level addressed the question of which groups of students think similarly or differently. Here, demographic identities such as gender and home or international status acted as moderators. As Q methodology does not model statistical interaction effects, our analysis treats intersectionality as a conceptual process in which multiple identity dimensions shape patterns of interpretation rather than as a demographic interaction to be quantified. Although intersectional analysis is more developed in education research (Harris & Patton, 2019), it remains less common in Q methodology. Recent calls for an intersectional lens emphasise the need to identify dynamic interactions between multiple factors that can contribute to discriminatory processes (Bešić, 2020). Our findings show that deep level cognitive orientations were more influential than surface level demographic identities. In several cases, perceived dominant identities were less important for factor alignment than underlying cognitive or interpretive patterns.
The third level emerged through the dialogue between Q methodology and focus group discussions. Only after seeing both differences and similarities across what students considered a diverse sample did participants articulate the perceived pressure to conform in order to mask a lack of belonging. This aligns with literature showing that belonging affects academic outcomes and general wellbeing (Allen et al., 2022), and with work by Fisher and Michiori (2021) and Matheson and Sutcliffe (2018), who emphasise the importance of environments that value diversity, encourage self-reflection, and support both individual and collective belonging. It is within this third level that the discussion of the following subsection on divergence as a structural feature of belonging is situated.
Divergence as a Structural Feature of Belonging
While we noted a majority viewpoint, we did not encounter consensus on how to work towards academic and employment success and how to feel belonging: Although the majority of student participants loaded on the Strategic Achiever factor, there was no overall consensus across all participants and the resulting factor landscape. Several factors endorsed themes such as fairness, recognition, and the belief that effort should matter, yet no statement achieved full agreement across all seven factors. This lack of consensus suggests that divergence is not a methodological artefact but a meaningful indication of the varied ways in which belonging is conceptualised and enacted within higher education.
Existing literature already anticipates such plurality. Research on recognition, competence, and relational acceptance shows that achievement can function as a basis for social acceptance (Allen et al., 2021b). Scholarship on institutional conformity highlights how belonging is constructed by social, institutional, political, and structural forces (Almarode et al., 2024, 2025). Work on moralised effort explains how stress and pressure can be reframed as indicators of commitment (Kundro, 2023). Studies on academic self-efficacy demonstrate that autonomy can operate as a protective strategy in uncertain environments (Korpershoek et al., 2020). The concept of cognitive belonging explains that some students experience belonging primarily through intellectual resonance rather than social connection (Mahar et al., 2013). Bourdieu's work on social reproduction illustrates how meritocratic beliefs can obscure structural inequality (Bourdieu, 1977; 1990). Research on the hidden curriculum has shown that students with fewer resources must navigate implicit expectations that are invisible to their more privileged peers (Koutsouris et al., 2021; Martin & Byrd, 2025). Studies of student precarity illustrate how unpredictable systems can erode trust and weaken participants’ sense of belonging (Borazon & Chuang, 2023; Reay, 2018; Reay et al., 2005).
These literatures align with the divergent patterns found in this study. Students interpreted shared ideals of fairness and recognition through highly distinct logics. For some, belonging was earned through discipline, ambition, or analytical engagement. For others, belonging was shaped by emotional and material strain, limited access to networks, or the perception that systems were opaque and inconsistent. The divergences therefore reflect not only personal worldviews but differing structural realities that shape how belonging becomes possible or constrained.
A significant system level issue also became evident. Despite strong institutional claims about promoting belonging, higher education offers only limited personalisation of learning or relational support. Participants across several factors expressed a desire for tailored academic guidance, structured opportunities for community building, and more intentional mechanisms for forming meaningful relationships. Students, particularly those managing financial pressures, care responsibilities, or commuting patterns (i.e., students who live at home and commute to university rather than living on campus or in shared student accommodations near campus), felt that universities expected them to form networks without accounting for their location, their limited time, or their resource constraints. This expectation was profoundly misaligned with many participants’ lived experiences and reinforced their detachment from campus life.
Taken together, the divergence patterns indicate that students and employers seek fairness, recognition, and legitimacy, yet encounter a system that continues to rely on an unstructured, one size fits all model of academic and social integration. Divergence should therefore be understood as a structural challenge for policy and practice, not as an individual difference for students to manage alone.
Methodological Implications
This study addressed three guiding questions: What do students and employers attribute as factors influencing their academic and professional success, does demographic group belonging shape the attribution of factors influencing their academic and professional success and how can our research findings help establish belonging in ways that do not just reveal the potential for belonging but help to establish the potential for belonging.
Q methodology addressed the first two research questions by showing how cognitive and emotional dimensions of belonging intersect with, but are not determined by, demographic identity. In response to the third research question, the reflexive use of Q methodology, supported by focus groups, highlighted the method's potential as both an analytical tool and a participatory practice that enables students to articulate, compare, and interrogate their own definitions of inclusion and belonging.
The study advances understanding by shifting analytical attention from demographic group membership to the cognitive and narrative structures through which belonging is interpreted in context. Through the combination of Q methodology and storytelling logic, the research shows how students and employers co-construct meaning around success and inclusion in ways that transcend demographic categories but remain shaped by structural inequality. The resulting seven factors illustrate how participants interpret belonging both as individual accomplishment and as relational recognition, exposing tensions between self-management and social connectedness that characterise many contemporary higher education environments. This contributes to a growing body of work that positions belonging as a dynamic process of sense-making and participation rather than a static outcome to be measured (Allen et al., 2021a, 2021b; Mahar et al., 2013).
Methodologically, integrating narrative interpretation and reflexive engagement extends conventional uses of Q methodology. Combining Q sorting with storytelling enabled participants to move between structured comparison and personal meaning making, translating abstract statements into lived experiences. This hybrid approach supports ethical and dialogical exploration of difference while identifying shared principles of belonging, and it advances methodological conversations about how belonging can be examined in participatory and context-sensitive ways. The approach demonstrates that Q methodology can serve not only as a device for accessing subjective orientations, but also as a reflective framework that helps participants understand their own cognitive positions in relation to others.
Practical Implications
The findings have already informed practice at both the focal business school and at the broader institutional level. Student liaison activities, focus group feedback systems, enhanced support for commuting students, and a newly created institutional position dedicated to student belonging, who has already organised a belonging “design jam”, all draw directly on the insights generated by the study. These developments have shaped Equality, Diversity, and Inclusion agendas and influenced the content of Freshers’ welcome talks, where students are encouraged to recognise the educational and professional value of diversity. This institutional emphasis mirrors the inclusion policies adopted by many graduate employers. For example, Deloitte (2025) notes that “we are convinced that we can best help our customers with a diversity of colleagues. After all, the problems they have are increasingly divergent,” illustrating how diversity is framed as integral to organisational effectiveness.
The underlying aim is to promote environments that acknowledge variation in cognitive orientations, resource constraints, and personal circumstances while resisting assumptions that students should independently navigate the academic and social dimensions of university life. This aligns with literature that highlights the importance of reflective, relational, and dialogical practices in cultivating belonging (Fisher & Michiori, 2021; Matheson & Sutcliffe, 2018). Through these practical applications, the study shows how belonging can be understood not simply as potential but as a process that institutions can scaffold deliberately. Students are invited to appreciate both difference and commonality within the student body, irrespective of demographic heterogeneity or homogeneity. This approach seeks to ensure that students feel empowered to express individuality without experiencing pressure to conform. The practical implications therefore reinforce the conceptual argument of the study, namely that belonging is constructed through interaction, interpretation, and institutional structures, and that meaningful change requires attention to all three.
Limitations and Opportunities for Further Research
While the analysis offers new insights into how belonging is negotiated, its scope and representativeness remain necessarily constrained by limited information, cognitive abilities, and time. This section reflects on these limitations and on directions for future research.
Some focus group statements reproduced cultural stereotypes, for instance the remark that “Asians are afraid of speaking.” Rather than taking such comments at face value, we interpret them as examples of how exclusionary discourses circulate within higher education environments. These narratives highlight the everyday misunderstandings and cultural assumptions that can reinforce marginalisation. Our reflexive stance recognises that the reproduction of such discourse in data does not represent fact but indicates the conditions under which students navigate belonging and exclusion. Following Rollock (2012) and Pillow (2003), we treat such utterances as interpretive artefacts that show how participants construct meaning in unequal contexts. By foregrounding such reflexivity, the study resists normalising stereotypes and instead frames them as part of the social texture that belonging research must interrogate.
This interpretive approach also underscores the ethical responsibility of researchers to interrogate their own role in knowledge production. As discussed earlier, the research team's positionalities as educators and social scientists inevitably shape both the interpretation of participant voices and the framing of theoretical insights. Maintaining critical reflexivity throughout the process allowed us to recognise the dialogical nature of belonging, where research practice itself becomes a site for ethical engagement.
While our analysis included demographic information on gender and home or international status, we did not conduct a full intersectional analysis in a statistical sense. Instead, our claims reflect an interpretive form of intersectionality, recognising how different identity dimensions inform participants’ sense-making without implying statistical interaction effects that the study design cannot evidence. The Q methodology approach therefore enabled us to explore cognitive intersectionality, that is, the ways in which different dimensions of identity awareness and personal experience intersect in shaping attitudes toward success and belonging. The emergent factors demonstrate that patterns of thinking often cut across demographic boundaries. Throughout the study we therefore offer an interpretive rather than predictive understanding of intersectionality.
The limited participation of Black home students constrains the breadth of the analysis and underscores a wider institutional issue. This underrepresentation reflects systemic disparities in who feels invited and safe to study at leading research-intensive universities and once there to participate in belonging research, echoing the findings of the UUK-NUS (2019) report on racialised inequalities in student outcomes. Addressing this imbalance requires institutional strategies beyond research design alone, including targeted inclusion efforts already at the time of recruitment, diverse research partnerships, and participatory forms of knowledge co production that engage underrepresented voices directly. Therefore, while the aim of the study was to provide insight into diversity, inclusion and belonging across a student body that encompasses several intersecting demographic characteristics, the number of Black home students was relatively small when compared with other home and international students. To explain the results we therefore focused on the home or international student divide. Further research is needed on the Black student segment, given that closing the BME awarding gap remains a central priority for UK universities (UUK-NUS, 2019).
As this research, like many other studies, focuses on correlations rather than causations and as it captures experiences at specific points in time, it is recommended that the research be repeated in future years, particularly to assess whether interventions influence students’ perceptions. Future studies that invite participation at university level, rather than at business school level, could also provide more nuanced attitudinal comparisons across a broader range of student groups.
Moreover, future research could explore whether the viewpoints identified in this study are associated with demographic or contextual variables by conducting comparative analyses across groups. For example, quantitative approaches such as ANOVA could examine whether different student populations systematically align with particular factors.
Education should be empowering and transformative by giving students and alumni the capability to shape their lives in ways they consider meaningful while recognising wider societal and environmental needs. The link between study experiences, including assessment cultures, and later work experiences and attitudes appears underexplored. Longitudinal studies would therefore be valuable in understanding how students reflect, with hindsight, on their higher education experiences and how these shape their careers, life trajectories and values.
Acknowledging these constraints helps to clarify the interpretive rather than generalisable nature of the study's contribution. The following conclusion summarises the key insights and their implications for inclusive practice and further inquiry.
Conclusion
This study examined which factors students and employers attribute to academic and professional success, whether demographic group membership shapes these attributions, and how the findings might help establish belonging in inclusive ways. The research also illustrated how cognitive and emotional dimensions of belonging intersect with, but are not determined by, demographic identity.
The reflexive and dialogical use of Q methodology, supported by focus group reflection, demonstrated how the method can be used to cultivate insight into diverse experiences of inclusion. Rather than producing definitive typologies of students, the research offers an interpretive framework through which belonging can be examined as a dynamic and relational process. The seven factors identified here represent situated patterns of negotiating recognition, performance and inclusion that can inform institutional dialogue rather than prescribe policy solutions.
Recognising inaccuracies and gaps in preconceptions in a system of dynamic relationships illustrates to students where they are like-minded, independent of whether they appear demographically diverse. Previous Q methodology research studies described in this paper are studies of a lack of belonging, while we move from researching the topic of belonging to establishing belonging. Usually, Q methodology focusses on a single dimension (the different viewpoints). As part of this study, we added a layer and included demographic characteristics as well as their intersectionality. By analysing sorting patterns at the intersection of home / international student categorisation and gender we were able to use Q methodology to develop a shared vision and consensus on recommendations for policy changes that resonated with students from different backgrounds.
Our research contributions are both at methodological and at practical level. We provide innovative insights into how educators can deploy Q methodology to develop a culture of belonging that respects students’ uniqueness and builds on consensuses. The focal UK business school of this study should be seen as microcosmic of many business schools and universities worldwide, many of which have a diverse international student body, with a need to (re)instil a sense of inclusion and belonging. Q methodology allowed us to move towards integration and connections of students and ideas to create synergies.
Furthermore, by deploying ready-off-the-shelf coding for this Q methodology research project, we aim for Q methodology to be perceived as a more accessible method for researchers and practitioners. We also add to the highly polarised discussion in the Q-community about whether research using Q methodology should follow exactly the methodology outlined by Stephenson in 1935 (e.g., Brown et al., 2015) or whether a purposeful adaptation of Q methodology, such as the one we have devised, can elicit additional results and can be seen as more accessible in the eyes of non-Q researchers.
Brown et al. (2015) compared researchers who doubt the validity of Q methodology with the Medicis who disbelieved Galileo. However, Brown et al. (2015) and other Q methodologists offer less insight into how to get non-Q methodologists, like the Medici family, to look through the Q methodological ‘telescope’. This study contributes to providing some of that missing incentive. We hope to increase the interest of the non-Q methodologists in Q methodology as well as to offer a tool for reflexivity for educators and students.
Footnotes
Acknowledgements
This manuscript is an original work that has not been submitted for publication elsewhere.
Ethical Considerations
Research ethics approval was sought and received from the participating institutions.
Consent to Participate
As part of the research ethics approval all participants gave informed consent prior to participating in this research.
Consent for Publication
Not applicable (covered as part of the research ethics approval).
Author Contribution(s)
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.