Undergraduate Achievement Disparities between Demographic Subgroups in English Universities

Abstract

In this paper, we report a comprehensive analysis of the disparities in undergraduate degree achievements across different demographic groups in English universities. The focus is on the “degree achievement gap”, which refers to the variation in the rates of students from diverse backgrounds obtaining First- or Upper Second-Class degrees. The significance of this gap lies in its profound impact on graduates’ future opportunities, particularly in terms of access to advanced studies and professional trajectories. Recognising the critical nature of this issue, the Office for Students (OfS) has emphasised the need for higher education institutions to actively work towards bridging this gap to enhance equity and social mobility. To map how far the call for bridging this gap has been effective, our research examines trends and patterns by age, ethnicity, disability, and gender over a five-year period from 2017/2018 to 2021/2022. Methodologically, this paper employs a detailed descriptive analysis. Our findings highlight a persistent and significant gap for Black students, who are consistently less likely to achieve a First- or Upper Second-Class degree when compared to their White peers. Based on the analysis, literature review, and policy mapping exercise, we make recommendations for the implementation of targeted support, student engagement, revisiting curriculum designs, and the promotion of a more inclusive campus culture. The insights and proposed strategies will be of interest to educators and policymakers.

1. Introduction

In England, the degree achievement gap (DAG), also known as the equity gap, is a critical issue in higher education, highlighting disparities in academic outcomes among different student groups. This gap is typically observed in the variation of degree classifications obtained by students from various demographic backgrounds, particularly when analysed through the lens of racial origins [1,2,3]. Notably, students from minority ethnic groups, especially those identifying as Black, frequently graduate with lower degree classifications when compared to their White counterparts. This ethnicity gap has become a focal point in numerous scholarly reports and policy documents, underscoring the urgent need for strategies to diminish these disparities as part of a broader commitment to social justice and equity in education [4].

The complexity of the DAG cannot be overstated, as it is influenced by a confluence of factors including institutional policies, teaching practices, and broader societal inequalities. Universities, along with policymakers, have embarked on various initiatives aimed at addressing this gap. These efforts encompass the call for inclusive teaching practices and affirmative action policies, such as enhancing access to support services for underrepresented students [5]. The Office for Students (OfS), a regulatory body overseeing the higher education sector in England, has been instrumental in setting ambitious targets for universities to reduce these gaps, with a particular focus on ethnic minority students [6].

Some higher education institutions have responded by developing mentoring schemes, academic support programs, and initiatives to cultivate a more diverse and inclusive campus culture. Furthermore, some universities have introduced “unconscious bias” training for staff and faculty, aiming to raise awareness of implicit biases and stereotypes that may inadvertently influence the academic performance of students from underrepresented groups [7]. These initiatives reflect a growing recognition of the multifaceted nature of the DAG and the need for comprehensive approaches to address it.

Despite these efforts, it remains imperative to critically evaluate the effectiveness of these strategies in narrowing the DAG. There are not many robust evaluations shedding light on the progress and challenges in this arena, and there are none suggesting that positive strides have been made, nor even showing that significant work remains. To address this gap, this paper aims to contribute to this ongoing discourse by mapping the patterns of degree classifications obtained by demographics during the last five years and examining the current state of the DAG in English universities. This kind of longitudinal tracking is useful in exploring the efficacy of implemented strategies and proposing further avenues for research and policy development.

In doing so, the study draws upon a rich body of literature that includes empirical research, policy analyses, and frameworks which are pertinent to higher education equity. By integrating insights from these diverse sources, the paper seeks to provide a comprehensive understanding of the DAG, its underlying causes, and the potential pathways towards more equitable educational outcomes for all students. This analysis is particularly timely and relevant, given the increasing emphasis on social mobility and the pivotal role of higher education in fostering a more just and inclusive society.

2. Literature Review

The literature surrounding the DAG in higher education in England is multifaceted [1]. Statistical report serves as a foundational document, offering comprehensive insights into student demographics and outcomes, and setting the stage for a deeper exploration of disparities in degree awarding, especially along the lines of ethnicity [2,8,9] and disability [6,10,11,12].

Ref. [13] utilised the self-determination theory to delve into the experiences of Black and minority ethnic (BME) students in higher education, underscoring the significance of autonomy, competence, and relatedness in academic success [13]. The work sheds light on intrinsic motivational factors and their impact on educational outcomes. In a similar vein, Ref. [3] challenges conventional perspectives on causality and inequality in degree outcomes, arguing that an overemphasis on individual student characteristics neglects systemic and institutional contributors to the achievement gap [3].

The burgeoning field of learning analytics offers another lens through which the DAG can be examined. Research reports critically assess the role of these analytics questioning the equity of existing algorithms and exploring the impact of predictive analytics on disadvantaged students in STEM fields [14,15]. This line of inquiry raises important questions about the intersection of technology and equity in education.

The issue of unconscious bias and its role in perpetuating the attainment gap is another critical area of focus. Ref. [7] highlights the necessity of addressing these biases in educational settings. Complementarily, research reports bring to the foreground the issue of systemic racism within universities, positing it as a key factor in the persistence of the achievement gap, particularly for BME students [16]. Ref. [17] contributes to this discussion by exploring student perceptions of the ethnicity degree awarding gap, revealing its complexity and the multifaceted nature of the problem as seen through the eyes of those most affected [17].

Degree awarding gaps in UK universities are driven by various interrelated factors [18]. These include unconscious bias, limited engagement opportunities with academic staff, institutional racism, inadequate support systems, and a lack of social and cultural capital. These elements collectively result in significant disparities in degree outcomes, particularly affecting students from lower socio-economic backgrounds and minority groups. The findings suggest that institutional practices and culture are crucial in either worsening or mitigating these disparities, underscoring the necessity for targeted interventions to address the underlying causes of degree awarding gaps.

Recommendations for addressing the gap are varied. The OfS suggests holistic changes, encompassing admissions policies, curriculum design, and student support services [6]. Ref. [9] proposes the use of peer research to deepen the understanding of the degree awarding gap in specific academic disciplines like geography, planning, geology, and environmental sciences [9].

Collectively, these studies paint a picture of a complex issue with deep-rooted causes and multifarious manifestations. They underscore the need for continued research to further elucidate these factors [10] and critically evaluate the effectiveness of interventions aimed at reducing the gap in degree outcomes. It is evident that the ongoing monitoring and evaluation of these initiatives are vital. Such efforts are essential not only for assessing their immediate effectiveness, but also for ensuring the sustained reduction of the degree awarding gap over time, thereby moving closer to an equitable higher education landscape in England.

3. Empirical Framework

The empirical framework for this paper was developed to ensure that the study is grounded in solid data analysis methods, providing reliable and actionable insights that can effectively inform policy and educational practice. The primary objective of this research was to comprehensively analyse the disparities in degree achievements among different demographic groups in English universities, focusing specifically on the DAG. This gap was defined as the variation in the rates at which students from diverse backgrounds obtain First- or Upper Second-Class degrees.

The data for this study were derived from university records spanning a five-year period from 2017/2018 to 2021/2022. These records provide detailed information on degree classifications awarded to graduates, segmented by demographic variables such as age, ethnicity, disability, and gender. For clarity and analysis, degree outcomes were categorised into five classifications as follows:

• First-Class Honours
• Upper Second Class (2:1)
• Lower Second Class (2:2)
• Third Class/Pass
• Unclassified

The framework employed a detailed descriptive analysis to quantify and illustrate the DAGs. This involved calculating the proportion of students in each demographic category who achieve each class of degree. Statistical measures were utilised to present the data comprehensively. To identify the demographic groups most significantly affected by the DAG, gap estimation techniques were employed. These techniques compared the rates of achieving Upper Second-Class or First-Class degrees across demographic groups, highlighting any statistically significant disparities. Through longitudinal trends analysis, trends and patterns over the observation period were analysed to observe the evolution of these disparities. This involved comparing annual data points to identify any shifts in the DAG, potentially indicating the impact of newly implemented educational policies or changing demographic profiles among students.

As we worked with population data, statistical tests, such as chi-square tests for categorical data and t-tests or ANOVA for continuous data, were not required to determine the significance of the observed differences in the degree outcomes across different groups. As some researchers argue, statistical tests of significance are redundant when the dataset is a census or covers the whole population, rather than a sample, because the findings pertain to all members of the population and thus do not require inferential statistics to be generalised [19].

Based on the findings, the study proposes specific interventions aimed at reducing the DAG. These recommendations are grounded in the observed data. The analysis culminates in a discussion that synthesises the findings with the broader implications for equity and social mobility in higher education. The study aims to provide a data-driven basis for policy and practice changes that can address and potentially mitigate the disparities in educational achievements.

4. Methods

4.1. Research Questions

This study employs an empirical approach to examine the disparities in educational outcomes upon the completion of degrees. The following research questions are designed to guide our analysis and help elucidate the factors contributing to these disparities:

• What are the trends in undergraduate degree classifications obtained by different demographic subgroups in England?
• How do characteristics such as ethnicity, gender, disability, and age contribute to the observed differences in the degree classifications obtained?

4.2. Research Design

This study is anchored in a cross-sectional research design framework, aimed at dissecting the nuances of the DAG across diverse undergraduate cohorts within English universities. Divergent from longitudinal studies that monitor the same set of individuals over an extended period, our cross-sectional approach involves a detailed examination of distinct student cohorts at singular time points. This investigation specifically encompasses an analysis of data from five unique cohorts, each representing the aggregate of students who completed their undergraduate degrees in successive academic years, spanning from 2017/2018 to 2021/2022.

The decision to opt for a cross-sectional design was strategically driven, with the objective of capturing temporal snapshots of varying subjects at specific, yet distinct, intervals. This methodology is particularly effective in facilitating comparisons across diverse groups at these discrete junctures. Our focus is centred on identifying and contrasting the degree achievements of different cohorts, rather than tracing the evolution or developmental trajectories within the same group over time.

This approach is instrumental in uncovering observable trends or emerging patterns across different cohorts over the years. However, it is imperative to acknowledge the inherent limitations of cross-sectional analysis, particularly its limited capacity in establishing causal relationships or tracking the progression of traits or outcomes within the same set of individuals over time. Consequently, the findings of this study must be interpreted with a degree of caution, especially in terms of drawing causal inferences. Despite these limitations, this research offers significant contributions to the discourse on educational equity within higher education. By analysing multiple cohorts, our study provides a comprehensive view of the evolving trends in degree achievement over time.

4.3. Data

The administrative data for this study were obtained from the Higher Education Statistics Agency (HESA), the official organisation responsible for collecting, analysing, and disseminating quantitative information about higher education in the United Kingdom. We selected this dataset to answer our research question due to HESA’s comprehensive data gathering and reporting platforms, which enable colleges, universities, and other higher education providers to submit their data to the organisation.

HESA has been pivotal in shaping UK higher education policies over the years. Policymakers have relied on its statistics for decisions concerning funding, research objectives, and other aspects of higher education. Collaborating with groups like the OECD and UNESCO, HESA has also contributed to the development of global standards for higher education statistics. Currently, HESA stands as a reliable source of data and analysis on higher education in the UK, providing information to a diverse array of stakeholders, including government organisations, higher education institutions, researchers, and the public. Its efforts continue to significantly influence policy and promote transparency and accountability in UK higher education.

This paper reports findings from our analysis of patterns in degree achievement and achievement gaps from 2017/2018 to 2021/2022. Our focus is on UK-domiciled, full-time, first-degree qualifiers and their degree classification (undergraduate students) in England. For each academic year, the number of student records analysed is summarised in

Table 1. Full-time students in England per academic year whose records were used for the analysis.

Academic year	2017/2018	2018/2019	2019/2020	2020/2021	2021/2022
Students	270,730	274,115	272,040	279,635	271,385

below.

4.4. Variables

In this study, we concentrated on four principal demographic factors as follows: gender, ethnicity, disability, and age. Gender was categorised into the two following groups: male and female. Due to their minimal representation in the dataset, students identifying as ‘other’ in gender were not included in this analysis. For ethnicity, our analysis was primarily focused on two distinct groups as follows: White and Black students. This decision was driven by the notably pronounced degree awarding gaps with distinct characteristics within these groups. Concentrating on these groups enables a more targeted exploration of the specific disparities at play.

In examining disability, students were classified into two categories as follows: disabled and non-disabled. This binary categorisation was adopted to facilitate a clearer comparative analysis of degree outcomes between these groups.

According to the Universities and Colleges Admissions Service (UCAS), a “mature student” in the context of undergraduate studies is typically defined as anyone who is over 21 years of age at the beginning of their undergraduate studies. This definition is commonly used in the UK higher education sector to differentiate older students from traditional-aged college students, who usually enter higher education soon after completing secondary education. Age was another critical demographic factor, with students being divided into two categories as follows: ‘traditional age students’, defined as those aged 21 years and below, and ‘mature students’, encompassing those aged over 21 years. This dichotomy allowed us to examine potential variances in degree achievements based on age categories.

The outcome variable, degree classification, was segmented into the four following groups: First-Class Honours, Upper Second-Class Honours, Lower Second-Class Honours, Third-Class Honours/pass, and unclassified. A First-Class Honours degree, colloquially known as a ‘First’, represents the highest level of achievement, an average grade of approximately 70% or higher. The Upper Second-Class Honours degree, commonly referred to as a ‘2:1’, ranks as the second highest. Regarded as a commendable academic attainment, it generally requires an average grade in the range of 60–69%. The classifications of ‘First’ and ‘2:1’ are particularly esteemed in the professional and academic realms, often constituting prerequisites for various postgraduate courses and favoured by employers. This preference is attributed to the perception that such classifications are indicative of a student’s capacity for high-standard performance, consistency, and quality output. It is noteworthy that this classification system, along with its specific percentage thresholds, is a distinctive characteristic of English universities.

4.5. Analytical Framework

For the comparative analysis, we employed descriptive statistics to detail the composition of all cohort differences in degree outcomes among demographic groups by ethnicity, gender, disability, and age. We calculated the percentage of students achieving the degree classifications (1st, 2:1 and above, lower second, and pass) by subgroups (White/Black, male/female, disabled/no known disability, mature/traditional age) in each category for each of the five years. For example, the percentage of females obtaining First-Class Honours divided by the total number of females who had a degree awarded led us to the percentage of females with First-Class Honours. After calculating similar percentages for males, we calculated the DAG for each classification. So, in this example, this was completed through subtracting the percentage of females obtaining First-Class Honours from the percentage of males obtaining First-Class Honours. This process was repeated for all degree classifications for gender.

Similarly, for the ethnicity gap, we subtracted the percentage of Black students from White students’ percentages for each classification. For the disability gap, we subtracted the percentage of disabled students in each category from those without any reported disability. Lastly, for age, we subtracted the percentage of mature students from the percentage of traditionally aged students.

Subsequently, as there were four categories of degree classifications, we estimated four achievement gaps for each variable per year. These have been referred to as DAG₁ for the percentage point difference in achieving First-Class Honours, DAG₂ for the percentage point difference in achieving Upper Second-Class Honours, DAG₃ for the percentage point difference in obtaining Lower Second-Class Honours, and DAG_P for those who passed with Third-Class Honours.

5. Results

Table 2. DAG for undergraduate courses 2017/2018, N = 270,730.

Markers		Percentages		Percentage Points Difference
		First-Class Honours (1)	Upper Second-Class Honours (U2)	DAG1	DAGU2
Gender	Male	28	46	−1	−3
	Female	29	49
Ethnicity	White	31	49	17	5
	Black	14	44
Disability	No	29	48	3	0
	Yes	26	48
	X ≤ 20	26	55	0	7
Age	X ≥ 21	28	48

,

Table 3. DAG for undergraduate courses 2018/2019, N = 274,115.

Markers		Percentages		Percentage Points Difference
		First-Class Honours (1)	Upper Second-Class Honours (U2)	DAG1	DAGU2
Gender	Male	27	46	−2	−3
	Female	29	49
Ethnicity	White	32	49	17	4
	Black	15	45
Disability	No	29	48	3	0
	Yes	26	48
Age	X ≤ 20	26	55	−3	7
	x ≥ 21	29	48

,

Table 4. DAG for undergraduate courses 2019/2020, N = 272,040.

Markers		Percentages		Percentage Points Difference
		First-Class Honours (1)	Upper Second-Class Honours (U2)	DAG1	DAGU2
Gender	Male	34	45	−2	−2
	Female	36	47
Ethnicity	White	38	46	18	−1
	Black	20	47
Disability	No	35	46	2	−1
	Yes	33	47
Age	X ≤ 20	34	52	−1	6
	x ≥ 21	35	46

,

Table 5. DAG for undergraduate courses 2020/2021, N = 279,635.

Markers		Percentages		Percentage Points Difference
		First-Class Honours (1)	Upper Second-Class Honours (U2)	DAG1	DAGU2
Gender	Male	35	45	−3	0
	Female	38	45
Ethnicity	White	40	45	19	−3
	Black	21	48
Disability	No	37	45	2	−1
	Yes	35	46
Age	X ≤ 20	36	51	−1	6
	x ≥ 21	37	45

and

Table 6. DAG for undergraduate courses 2021/2022, N = 271,385.

Markers		Percentages		Percentage Points Difference
		First-Class Honours (1)	Upper Second-Class Honours (U2)	DAG1	DAGU2
Gender	Male	30	45	−3	−1
	Female	33	46
Ethnicity	White	36	46	18	1
	Black	18	45
Disability	Yes	32	46	0	1
	No	32	45
Age	X ≤ 20	30	52	0	7
	x ≥ 21	30	45

in this paper offer a nuanced analysis of the proportion of students attaining First- or Upper Second-Class (2:1) Honours in their undergraduate courses across the last five years. These tables disaggregate the results by key demographic groups, thereby presenting a holistic view of degree achievement trends among these populations. The analyses for the academic years 2017/2018 (Table 2) and 2018/2019 (Table 3) reveal a general parity in academic achievements within gender and disability subgroups. However, noticeable disparities emerge in good degree classifications when scrutinising ethnicity and, to some extent, age demographics. For a more detailed breakdown, refer to the Appendix A, which include

Table A1. Degree awarding gaps for undergraduate courses 2017/2018, N = 270,730.

Markers		Percentages					Percentage Points Difference
		First-Class Honours (1)	Upper Second-Class Honours (U2)	Lower Second-Class Honours (L2)	Third-Class Honours/Pass (P)	Unclassified	DAG1	DAGU2	DAGL2	DAGP
Gender	Male	28	46	19	4	3	−1	−3	3	1
	Female	29	49	16	3	3
Ethnicity	White	31	49	14	2	3	17	5	−18	−6
	Black	14	44	32	8	2
Disability	No	29	48	17	3	3	3	0	−2	−1
	Yes	26	48	19	4	3
	X ≤ 20	26	55	16	2.5	0.5	−2	7	−1	−2
Age	x ≥ 21	28	48	17	3.5	3.5

and

Table A2. Degree awarding gaps for undergraduate courses 2018/2019, N = 274,115.

Markers		Percentages					Percentage Points Difference
		First-Class Honours (1)	Upper Second-Class Honours (U2)	Lower Second-Class Honours (L2)	Third-Class Honours/Pass (P)	Unclassified	DAG1	DAGU2	DAGL2	DAGP
Gender	Male	27	46	19	4	4	−2	−3	3	1
	Female	29	49	16	3	3
Ethnicity	White	32	49	14	2	3	17	4	−17	−6
	Black	15	45	31	8	2
Disability	No	29	48	17	3	3	3	0	−2	−1
	Yes	26	48	19	4	3
Age	X ≤ 20	26	55	17	2	0	−3	7	0	−1
	x ≥ 21	29	48	17	3	3

.

Consistent patterns in degree classifications were observed for the academic years 2019/2020 (Table 4), 2020/2021 (Table 5), and 2021/2022 (Table 6), with gender and disability groups showing similar trends. However, as was the case in previous years, disparities in the attainment of higher classifications were notable across ethnicity and age groups. These findings, detailed in Table 4, Table 5 and Table 6 and their respective Appendix A (

Table A3. Degree awarding gaps for undergraduate courses 2019/2020, N = 272,040.

Markers		Percentages					Percentage Points Difference
		First-Class Honours (1)	Upper Second-Class Honours (U2)	Lower Second-Class Honours (L2)	Third-Class Honours/Pass (P)	Unclassified	DAG1	DAGU2	DAGL2	DAGP
Gender	Male	34	45	15	3	3	−2	−2	2	1
	Female	36	47	13	2	3
Ethnicity	White	38	46	11	2	3	18	−1	−15	−3
	Black	20	47	26	5	2
Disability	No	35	46	13	2	3	2	−1	−1	0
	Yes	33	47	14	2	3
Age	X ≤ 20	34	52	12	1	1	1	6	−2	−1
	x ≥ 21	35	46	14	2	3

,

Table A4. Degree awarding gaps for undergraduate courses 2020/2021, N = 279,635.

Markers		Percentages					Percentage Points Difference
		First-Class Honours (1)	Upper Second-Class Honours (U2)	Lower Second-Class Honours (L2)	Third-Class Honours/Pass (P)	Unclassified	DAG1	DAGU2	DAGL2	DAGP
Gender	Male	35	45	14	3	3	−3	0	2	1
	Female	38	45	12	2	3
Ethnicity	White	40	45	11	2	2	19	−3	−14	−2
	Black	21	48	25	4	2
Disability	No	37	45	13	2	3	2	−1	0	0
	Yes	35	46	13	2	3
Age	X ≤ 20	36	51	12	1	0	−1	6	−1	−1
	x ≥ 21	37	45	13	2	3

and

Table A5. Degree awarding gaps for undergraduate courses 2021/2022, N = 271,385.

Markers		Percentages					Percentage Points Difference
		First-Class Honours (1)	Upper Second-Class Honours (U2)	Lower Second-Class Honours (L2)	Third-Class Honours/Pass (P)	Unclassified	DAG1	DAGU2	DAGL2	DAGP
Gender	Male	30	45	17	4	4	−3	−1	2	1
	Female	33	46	15	3	3
Ethnicity	White	36	46	13	2	3	18	1	−14	−5
	Black	18	45	27	7	3
Disability	No	32	45	16	3	4	0	1	0	0
	Yes	32	46	15	3	4
Age	X ≤ 20	30	52	16	2	0	−2	7	0	−1
	x ≥ 21	32	45	16	3	4

), suggest enduring challenges or systemic barriers particularly affecting mature and Black students’ educational outcomes. This persistent discrepancy underscores the need for targeted strategies to address these educational disparities.

The data consistently reveal that Black students are less likely to receive higher degree classifications when compared to their White counterparts. This trend is strikingly illustrated in Figure 1 and Figure 2. Figure 1 shows that the percentage of White students achieving First-Class Honours is nearly double that of Black students, a gap that has remained consistent over the five years. Figure 2 further demonstrates that a higher percentage of White students achieve either First-Class Honours or Upper Second-Class Honours, indicating a persistent disparity in ‘good’ degree classifications between White and Black students. These findings underscore the need for further investigation and interventions to address the evident inequities in educational outcomes among different ethnic groups.

6. Discussion of Results and Implications for Practice

This paper’s comparative analysis over the last five years reveals trends in the DAG, noting the impossibility of making causal claims from this study design. The findings and literature reviewed for the paper indicate the need to address institutional reasons for the equity gap, particularly the attainment disparity between Black and White students in higher education. In response to the recent announcement of the UK government’s plans to drive change in tackling inequalities among different groups, universities were held accountable through their Access and Participation plans, and university league tables were pressured to include the progress made in addressing attainment and access disparities in their rankings [8]. However, there is a significant lack of longitudinal and trajectory research to assist in understanding the progress of various groups of students. Our analysis recognises potential statistical evidence and portrays the situation by investigating the degree attainment gap in a comprehensive way.

It was announced in late 2018 that the OfS, the Independent Regulator for higher education in England, had set new national targets for achieving equality of opportunity by addressing the degree award gaps in higher education [6]. Based on the findings of this study, the purpose of this brief analytical report is to encourage policymakers and educators to assess the effectiveness of these national targets for achieving equality. We show that a gap still exists regarding ethnicity and age, and perhaps other student background indicators not analysed here, such as socio-economic status (the data for which was not available to us from HESA).

In the literature, many studies have investigated the degree awarding gap across different contextual indicators and explored ways to reduce this gap in various subject majors [9,13,14,15,17]. One common issue in these studies is that they mainly focus on a single contextual indicator, ignoring the fact that more than one factor can be considered as an intersection. In other words, a multivariate data relationship analysis is used to measure the relationship between variables. This approach is imperfect in understanding degree award gaps. It assumes that, regardless of, for example, racial categorisation, variables are interrelated in the same manner [16].

Researchers have suggested that there should be a measurement of degree awarding gaps across different locations of social intersection. Ref. [10] supported the use of an intersectional approach, which aims to understand human experience as being shaped by multiple social positions (e.g., racial and gender positions) simultaneously, rather than considering these positions separately. Intersectionality enhances analytical sophistication and provides theoretical explanations regarding how heterogeneous members of specific groups may experience universities differently depending on their ethnicity, disability, class, or other social circumstances. By being sensitive to such differences, we can gain a deeper understanding of issues of social justice and inequality in higher education and institutions, which increases the likelihood of social change [11,12]. However, the concept of intersectionality has not been extensively studied in degree awarding gap studies in the UK so far.

One more important point is that, to complement the existing research on awarding gaps, it is important to respect and consider the individuality of universities based on their structural and socio-cultural characteristics. Due to the complexity and intersectionality of the issues, there are no silver bullets or straightforward solutions, particularly when considering the differences within minority ethnic groups [17]. There will be a need for a variety of policies and initiatives aimed at addressing specific inequalities that contribute to unequal degree outcomes. This includes considering differences across degree disciplines, as well as the design of the curriculum and assessments, while also considering intersectionality—an issue currently lacking in the literature. In other words, a major challenge that needs to be better recognised by individuals at all levels, including institutions, is the acceptance of intersectional analysis, which requires a collective effort.

To the best of our knowledge, the degree awarding gap in England has not been studied considering intersectionality. Future studies could focus on intersectionality in degree awarding gaps to gain a better understanding and to address this complex problem. Moreover, educators or institutions that strive to be inclusive must reflect upon the composition of their cohorts and the perspectives they bring to the classroom. It should be noted, however, that regardless of the intersectionality of diverse identities within our learning audiences, culturally appropriate material must be included.

From a methodological perspective, a recent paper by highlights the longstanding concern regarding student outcomes in the higher education sector and the UK government for more than a decade [3]. The OfS has made it a priority since its inception in 2018 to require institutions to evaluate the effectiveness of their initiatives as defined in their Access and Participation Plans, providing evidence of causality [6]. This policy development is a response to several reports that have identified a lack of evidence-based interventions and a lack of knowledge regarding what works for different sub-groups. Therefore, conducting well-designed randomised controlled trials (RCTs) is essential from both theoretical and statistical perspectives. It is important to employ econometric analysis techniques, such as propensity score matching and propensity score weighting, even when using administrative data, instead of solely relying on associations or relationships between concepts. Overall, while degree awarding gaps may not be eliminated (but can be narrowed) even with the implementation of different policies and strong interventions, we can gain a better understanding of them and address them more directly through employing a holistic mix of measurement methods, causal analysis, and an intersectional perspective.