Undergraduate retention and attainment
across the disciplines
Ruth Woodfield
Contents
Section
Page
Executive summary
3
Introduction
5
Key findings
8
Retention across the disciplines
8
Attainment across the disciplines
10
Undergraduate retention and attainment across the disciplines
12
Section one – student characteristics by disciplinary area
12
1.1 Socio-demographic characteristics of students
14
1.2 Characteristics associated with students’ study
33
Section two - retention and attainment across the disciplines
42
Retention
42
Attainment
58
Conclusion
69
References
70
Appendices
71
Appendix 1 - List of HEA disciplines
71
Appendix 2 – Retention and attainment data set
74
Appendix 3 - HESA definitions non-continuation marker
76
Appendix 4 - Background information on key demographic
groups: nations
77
2
Executive summary
1 Participation in HE has increased substantially over the past two decades, as have the rates at
which students continue with their studies, and attain a first or upper second in their degree
(HEFCE 2014)1. Yet recent research indicates that students from diverse backgrounds
participate, persist and attain in HE at different rates, and that such differences can be explained
with reference to a range of student characteristics, as well as practices within HE itself (Boliver
2014; HEFCE 2013, 2014; HEA 2011; ECU 2008).
2 This study contributes further to the body of existing research by focusing primarily on the role
of disciplines2 in this overall picture, and how students from a variety of backgrounds perform
against the key indicators of retention and attainment within different disciplinary contexts. The
report presents an analysis of official data3 relating to undergraduate students participating in
higher education in the academic year 2010-11, and includes all students who were taking a
degree in a single, identifiable discipline (n = 1,631,468).
3 The report includes consideration of a range of students’ background characteristics as well as
a range of characteristics associated with students’ study: age; gender; socio-economic
class/parental education level; ethnicity; disability status; mode of study (part-time/full-time);
pre-HE country of domicile; UCAS points attained; distance between pre-HE address and
higher education institute (HEI); nation of HEI.
4 This study identifies that the composition of the student body varies considerably across
disciplines. Students who differed by key background characteristics – for example, age,
ethnicity, gender – were distributed unevenly across the disciplinary spectrum.
5 Particular student background characteristics were linked to heightened levels of vulnerability
to lower continuation and/or lower attainment rates. These included being a man, being from
specific BME backgrounds, being from a lower socio-economic class, being a mature student,
studying part-time and studying at a more local HEI.
6 Moreover, differences within disciplines themselves influenced divergent continuation and
attainment rates, both independently and when interacting with student characteristics. Some
disciplines had retention rates of 93% while other had rates of 99%, and clearly students from a
variety of backgrounds are more likely to withdraw without their degrees if they are in a
discipline with lower overall retention rates. However, even across disciplines with the same
retention rates, students with the same background characteristics were more likely to
withdraw from one discipline than the other. For instance, Marketing and Built Environment
shared the same overall withdrawal rate of 6%, yet, in the case of Marketing, part-time students
were over four times as likely to have withdrawn without their degree than their full-time
counterparts, while in Built Environment, little difference existed between part-time and fulltime students’ withdrawal rates. Findings such as these raise questions about the underlying
causes of disciplinary differences in retention rates.
1
For convenience, the report throughout refers to ‘upper degree’
See Appendix 1 for a list of the 30 Higher Education Academy (HEA) disciplinary areas, as well as the sub-disciplinary
subjects comprising each broad discipline.
3
Bespoke Higher Education Statistics Agency (HESA) data set: 34843_RL (2013) – please see Appendix 2 for further
information on the sample.
2
3
7 Besides differences in withdrawal rates, differences in students’ recorded reasons for
withdrawal were observable across individual disciplines and their broad academic umbrella
areas. For instance, the majority of Science, Technology, Engineering and Mathematics (STEM)
disciplines, as well as the majority of social science disciplines, recorded higher than average
percentages of students leaving for ‘academic failure’ reasons, while the majority of Arts and
Humanities disciplines recorded lower percentages of students leaving because they failed to
progress. High academic failure rates themselves are of concern as specific groups of students –
for example, most groups of BME students – were revealed to be particularly vulnerable to this
exit route.
8 There was also considerable variation across the disciplines in terms of attainment. All but one
discipline (Art and Design), within the broad Arts and Humanities, area recorded higher rates
of upper degrees than the sector as a whole. Five out of eight STEM disciplines also recorded
higher rates of upper degrees. By contrast, seven out of nine Social Science disciplines had
lower rates of upper degrees than the sector as a whole, while disciplines within health and
social care were evenly split. As was the case with varied continuation rates, divergent
attainment rates across disciplines could not be simply or wholly explained with reference to
student characteristics. So that, for example, although part-time students had lower attainment
levels overall as compared to full-time students, in Economics, Finance and Accounting,
Marketing, Music, Dance and Drama, and Politics specifically, the lead full-time students had
over part-timers in the attainment of an upper degree was 30% or higher.
9 The report’s findings point to a complex mix of factors that lead to different continuation and
attainment rates across disciplines. It provides an overview of disciplinary differences for those
working and studying within HE, and suggests such differences constitute an important part of
the HE landscape that we should seek to understand better if we are committed to the reality
of “widening access and achieving student success” across a “diverse student body”, as well as
to the principle of supporting “a vibrant and cohesive intellectual, social and cultural
environment” in our universities (BIS 2014, p. 4).
4
Introduction
This report explores disciplinary differences in higher education (HE). It concerns differences
within the student body, and focuses on student continuation and attainment patterns across
disciplinary areas. It presents an analysis of official data4 relating to undergraduate students
participating in higher education in the academic year 2010-11, and includes all students who were
taking a degree in a single, identifiable discipline (n = 1,631,468).
The report includes consideration of a range of students’ background characteristics as well as a
range of characteristics associated with students’ study:










age;
gender;
socio-economic class/parental education level;
ethnicity;
disability status;
mode of study (part-time/full-time);
pre-HE country of domicile;
UCAS points attained;
distance between pre-HE address and higher education institute (HEI);
nation of HEI.
The report explores how the student body in each discipline is configured differently according to
these characteristics, and how such characteristics, as well as the disciplines themselves, are linked
to variations in retention and attainment rates.
Participation in HE has increased substantially over the past two decades, as have the rates at
which students continue with their studies, and attain a first or upper class degree (HEFCE 2014).
Yet recent research indicates that students from diverse backgrounds participate, persist and
attain in HE at different rates, and that such differences can be explained with reference to a range
of student characteristics, as well as practices within HE itself (Boliver 2014; HEFCE 2013, 2014;
HEA 2011; ECU 2008). This study contributes further to the body of existing research by focusing
primarily on the role of disciplines in this overall picture, and how students from a variety of
backgrounds perform against the key indicators of retention and attainment within different
disciplinary contexts.
This study identifies that the composition of the student body varies considerably across
disciplines, so that students who differed by key background characteristics were distributed
unevenly across the disciplinary spectrum. We see, for example, that traditional age students
constituted 60% of the student body across the whole sector but represented over 80% of the
students in some disciplines (e.g. Economics, Marketing, Media and Communications) and less than
30% in others (e.g. Nursing, Social Work and Social Policy). Similarly, while men represented 43%
of the student body as a whole, they were over-represented in some disciplines and underrepresented in others, accounting for over 80% in Computer Science, and Engineering but 20% or
less of students in Education, Nursing, Social Work and Social Policy. Each discipline explored here
had its own specific profile that reflected the shape of its student body and the range of (often
intersecting) characteristics they brought with them. The profile of Economics students was, for
4
Bespoke Higher Education Statistics Agency (HESA) data set: 34843_RL (2013) – please see Appendix 2 for further
information on the sample.
5
instance, over 90% traditional age, 69% male, with higher than average percentages of Black and
minority ethnic (BME) students, students from socio-economic classes one and two, those
studying full-time and those selecting HEIs that were further than 30 miles from their pre-HE
address. By contrast, the profile for Education students was markedly different; over 60% of
Education students were mature age, over 80% were women, with higher than average levels of
students from lower socio-economic classes, White and part-time students, as well as those
selecting an HEI close to their pre-HE address.
Particular student background characteristics were linked to heightened levels of vulnerability to
lower continuation and/or lower attainment rates. These included being a man, being from specific
BME backgrounds, being from a lower socio-economic class, being a mature student, studying
part-time and studying at a more local HEI. The fact that such characteristics were linked to
differential retention and attainment rates does not necessarily imply causation. It may be that one
‘vulnerability’ characteristic (e.g. being a man) might intersect with others not linked to
vulnerability (e.g. being young; being from a higher socioeconomic background; studying full-time,
etc.). Alternatively, some ‘vulnerability’ characteristics may be linked to shared common variables;
for example, being a mature student may increase the likelihood of students having caring
responsibilities, meaning that these students are more likely to live locally, study part-time, etc.,
and that their retention and attainment may be likely to be adversely affected by their other
responsibilities. This might explain why, despite its specific gender profile, students in Economics
have higher rates of continuation and attainment than sector averages.
Moreover, differences within disciplines themselves influenced divergent continuation and
attainment rates, both independently and when interacting with student characteristics. Although
all disciplines had continuation rates of over 90%, some (e.g. Engineering) fell at the bottom end of
the spectrum with a rate of 93%, while others (e.g. Medicine and Dentistry) fell at the top with
99%. Clearly, students from all backgrounds are more vulnerable to withdrawing from their
courses without their degrees if they are studying within a discipline with an overall withdrawal
rate of 93% as opposed to a withdrawal rate of 99%. However, even when overall retention rates
were the same across specific disciplines, interesting and important differences in withdrawal
patterns were observable. Consequently, while Marketing, and Built Environment shared the same
overall withdrawal rate of 6%, in the case of the Marketing, part-time students were over four
times as likely to have withdrawn without their degree than their full-time counterparts, yet in
Built Environment, little difference existed between part-time and full-time students’ withdrawal
rates. Findings such as these raise questions about the underlying causes of disciplinary differences
in retention rates. Do they primarily reflect disparities related to curriculum, custom or culture or
an interaction between all three factors? In some cases, curriculum-related reasons do not seem
sufficient to explain the performance of different groups across disciplines. For instance, there
were similar (albeit small) numbers of ‘Black or Black British – Caribbean’ students in Philosophy
and Religious Studies and Maths and Statistics, but 24% of them withdrew without their award
from the former discipline, while only 3% did so from the latter.
Besides differences in withdrawal rates, differences in students’ recorded reasons for withdrawal
were observable across individual disciplines and their broad academic umbrella areas5. For
5
HEA STEM disciplines comprise: Biological Sciences; Built Environment; Computer Science; Engineering; GEES; Maths
and Statistics and Operational Research; Physical Science; Psychology.
HEA Social Science disciplines comprise: Business and Management; Economics; Education; Finance and Accounting;
Hospitality, Leisure, Sport and Tourism; Law; Marketing; Politics; Sociology.
HEA Arts and Humanities disciplines comprise: Art and Design; English; History; Languages; Media and
Communications; Music, Dance and Drama; Philosophy and Religious Studies.
6
instance, the majority of Science, Technology, Engineering and Mathematics (STEM) disciplines, as
well as the majority of Social Science disciplines, recorded higher than average percentages of
students leaving for ‘academic failure’ reasons, while the majority of Arts and Humanities
disciplines recorded lower percentages of students leaving because they failed to progress. While
some disciplines with high rates of students withdrawing because of academic failure also had high
rates of continuation overall (e.g. Economics; Medicine and Dentistry), high academic failure rates
themselves are of concern as specific groups of students were revealed to be particularly
vulnerable to this exit route. For example, most groups of BME students were more likely than
White students to withdraw for academic failure reasons.
There was also considerable variation across the disciplines in terms of attainment. All but one
discipline (Art and Design) within the broad Arts and Humanities area recorded higher rates of
first or upper second in their degree (hereafter upper degree) than the sector as a whole. Five
out of eight STEM disciplines also recorded higher rates of upper degrees. By contrast, seven out
of nine Social Science disciplines had lower rates of upper degrees than the sector as a whole,
while disciplines within Health and Social Care were evenly split. Attainment rates varied widely
across disciplines from those where 75% or more of students achieved an upper degree (e.g.
History, English, Music, Dance and Drama, Philosophy and Religious Studies), to those where less
than 60% achieved one (e.g. Business and Management, Computer Science, Hospitality, Leisure,
Sport and Tourism, Nursing and Social Work and Policy). As was the case with varied
continuation rates, divergent attainment rates across disciplines could not be simply or wholly
explained with reference to student characteristics. So that, for example, although part-time
students had lower attainment levels overall as compared to full-time students, in Economics,
Finance and Accounting, Marketing, Music, Dance and Drama and Politics specifically, the lead fulltime students had over part-timers in the attainment of an upper degree was 30% or higher. Why
should this be the case? It was not simply because part-time students themselves brought
additional vulnerabilities with them to these disciplines; indeed, other than their part-time status,
they varied considerably across them. In Economics, for example, part-time students were 65%
male, 47% mature and 23% reported a parent with an HE qualification. By contrast, in Music,
Dance and Drama they were 43% male, 62% mature and 18% reported a parent with an HE
qualification. The fact that part-time students in both of these disciplines in particular recorded
much lower attainment rates than the sector average raises further questions about the divergent
contexts that specific disciplines provide for students to study within.
The report’s findings point to a complex mix of factors that lead to different continuation and
attainment rates across disciplines, and to the need to further explore curricula, cultures and
practices at the disciplinary level, and how these interact with student characteristics if we are
committed to the reality of ‘widening access and achieving student success’ across a ‘diverse
student body’ (BIS 2014: 4).
HEA Health and Social Care disciplines comprise: Health; Medicine and Dentistry; Nursing; Social Work and Policy;
Veterinary Medicine.
7
Key findings
Retention across the disciplines
a. Across the sector as a whole 94% of students either had continued with their studies or had
successfully completed their studies. Disciplines with the highest continuation rates – of 97%
or above – included Economics, Geography, earth and environmental sciences (GEES),
History, and Medicine and Dentistry. Three disciplines had comparatively low continuation
rates: Computer Science (91%), Hospitality, Sport, Leisure and Tourism (92%), and
Languages (92%).
Some student characteristics were linked to increased rates of non-continuation:
i. Sector-wide, a larger percentage of mature students (7%) than traditional age students
(5%) left without their award. Mature students withdrew more often than their
traditional counterparts in all disciplines except Maths and Statistics, Nursing, Social
Work and Policy, and Veterinary Medicine. In Law, Marketing, Philosophy and Religious
Studies, and Physical Science, mature students were twice as likely to leave without
their award than their traditional age counterparts.
ii. A higher percentage of men (7%) than women (5%) withdrew without their award
across the sector. Higher percentages of men withdrew across all disciplines except
Other6, Physical Science and Veterinary Medicine.
iii. Sector-wide and across most disciplines those identified as being from socio-economic
classes one and two were slightly less likely to withdraw than other students. Similarly,
sector-wide and across most disciplines, those students who reported a parent with an
HE qualification were slightly less likely to withdraw without their award than students
without a parent with HE qualifications.
iv. A student’s ethnic background was related to their continuation rate. Looking at the
broad differences across the sector overall, White (6%) students were less likely than
BME (8%) students to leave without their award. In terms of disciplinary differences,
BME students overall recorded lower levels of continuation in all disciplines than did
White students. There were important differences within the broad category of BME
students, however, so that, with few exceptions, Chinese students recorded the lowest
levels of non-continuation across most individual disciplines, followed by White
students and students from ‘Asian or Asian British – Indian’ background. Wide
variations in non-completion rates across the full range of disciplines emerged among
most sub-groups of students from BME backgrounds. For instance, while the withdrawal
rate for ‘Black or Black British – Caribbean’ students from Maths and stats was 3%, it
stood at 24% for Philosophy and Religious Studies.
v. Across the sector as a whole, students reporting a disability were no more likely (6%)
than students not reporting one (6%) to leave without their award. However, in 19/30
disciplines students with a disability were slightly (1% or 2%) more likely to leave
without their award. In two disciplines – Music, Dance and Drama, and Other –
students with a disability were 1% less likely than students without a reported disability
to withdraw without their award.
vi. Overall part-time students (8%) were more likely than full-time students (5%) to
withdraw without their award. In all disciplines except Maths and Statistics, Other,
6
Students taking combined degrees under the discipline ‘Other’ were included in this analysis as these students were
not associated with any of the other HEA disciplines but were rather associated with the area of Combined or Other
Studies.
8
b.
c.
d.
e.
Psychology, and Veterinary Medicine, part-time students were more likely to leave
without their award. In some disciplines, the gap between part-time and full-time
students was substantial.
vii. Overall, 5% of students domiciled within the EU before commencing their studies
withdrew without their awards, while 6% of students domiciled outside of the EU and
the UK did so. The effect of the country of domicile on retention was not uniform. In
some disciplines, in Education for instance, 33% of students from non-European
countries left without their award as against 7% of students from EU countries and the
UK. In other disciplines, however (for example Law, Maths and Statistics, Veterinary
Medicine), students from non-European countries were less likely to leave their courses
than students domiciled in the UK before their studies.
viii. In terms of the sector overall, students with 340 UCAS points or above were
considerably less likely (4%) than those with less UCAS points (9%) to leave their
courses without their award. In all disciplines, except for Other, students with 340
points and above withdrew less often. In 17/30 of the individual disciplines, they
withdrew at half the rate of their counterparts with less than 340 points.
ix. Overall, students who attend a university that was 30 miles or less away from their preHE address (8%) were more likely to withdraw without their award than students who
attend a university further afield (5%). With the exception of two disciplines – Medicine
and Dentistry and Social Work and Policy – students who attended a more local
university were more likely to withdraw without their award across all disciplines. This
trend was more marked in certain disciplines such as Economics, Languages, Other,
Sociology, and Veterinary Medicine.
x. The nation within which students studied was also linked to different continuation/noncontinuation rates. Overall, Northern Ireland had the lowest non-continuation rate of
just 3%, followed by England and Scotland, with rates of 6%, and finally, Wales, with a
rate of 11%. Northern Ireland saw the lowest percentages of students leaving without
their award across most disciplines. Wales was the nation with the highest percentages
of students withdrawing without their award in most disciplines.
There are a number of interesting differences between the disciplines in respect of students’
reasons for withdrawing without their award. Students who had failed to progress
academically were the largest (29%) sub-category of leavers. The majority of STEM
disciplines, as well as the majority of Social Science disciplines, recorded higher percentages
of students leaving for this reason than the sector average, while the majority of Arts and
Humanities disciplines record lower than average percentages of students leaving because
they failed to progress academically.
i. Some groups of students were over-represented within the group of leavers that failed
academically. These included men, students from socio-economic classes three to nine,
traditional age students and BME students. The strongest case of over-representation
occurred in relation to BME students where all groups of students from ethnic minority
backgrounds, except ‘Chinese’ students, were over-represented in the category of
students who leave their course through academic failure.
‘Other personal’ reasons for leaving accounted for the second largest group of students
withdrawing without their award. Against a sector rate of 22%, some disciplines had notably
higher percentages of students in this category, namely History (32%), Languages (34%),
Music, Dance and Drama (32%) and Philosophy and Religious studies (32%).
All disciplines recorded that less than 3% of their non-continuation students had left
because of financial reasons.
Against a sector rate of 4% of students leaving due to ‘Exclusion’, some disciplines showed
rates twice as high or more; these were GEES (9%), History (10%), Other (9%), Politics
9
(8%), Social Work and Policy (9%) and Sociology (8%). One discipline – Veterinary Medicine
– recorded no students leaving because of exclusion.
i. Overall, mature students, men, students from socio-economic classes three to nine and
students without a parent with HE qualifications, and BME students were overrepresented in the category of students excluded from their courses. Chinese students
were the only ethnic minority group not over-represented in this category of leavers.
Attainment across the disciplines
a. Across the sector as a whole, 65% of students achieved an upper degree. There were wide
variations across disciplines in terms of the achievement of upper degrees, however, so that
80% of students within History, 78% in Languages, 76% in English and 88% in Medicine and
Dentistry achieved one, while under 60% of students in Business and Management and
Computer Science, Hospitality, Leisure, Sport and Tourism, Nursing, and Social Work and
Policy did so.
Some student characteristics were linked to lower rates of upper degree attainment:
i. Age was linked to students’ achievement of an upper degree. Overall, 66% of traditional
age students achieved an upper degree as against 61% of mature students. In 22/30
disciplines, traditional age students achieved a higher rate of upper degrees than mature
students, and the age attainment gap was considerable in some disciplines. For instance,
in Economics, 70% of traditional students achieved an upper degree as against 51% of
mature students, and in Marketing, 65% of traditional students achieved one against 48%
of mature students.
ii. Overall, 67% of women achieved an upper degree against 62% of men. Women
achieved higher percentages of upper degrees in 27/30 disciplines; the exceptions being
Built Environment, Philosophy and Religious Studies, and Social Work and Policy. The
gender attainment gap was considerable in some disciplines. For example, it was13 to
14% in GEES, Hospitality, Leisure, Sport and Tourism, Marketing, and Veterinary
Medicine.
iii. Overall, 71% of students from socio-economic classes one and two achieved an upper
degree, while 65% of students from socio-economic classes three to nine achieved one.
In 27/30 disciplines, students coming from socio-economic classes one and two were
more likely to secure an upper degree than students coming from socio-economic
classes three to nine.
iv. Similarly, overall, 70% of students reporting a parent with HE qualifications achieved an
upper degree, as against 64% of students reporting no parent with HE qualifications. In
all disciplines except Computer Science, Medicine and Dentistry, and Physical Science,
students with a parent with an HE qualification were more likely to have achieved an
upper degree.
v. Ethnicity was related to attainment. Overall, 70% of White students and 52% of BME
students achieved an upper degree. In all but eight disciplines, a higher percentage of
White students achieved an upper degree than BME students – the exceptions were:
GEES, History, Hospitality, Leisure, Sport and Tourism, Law, Marketing, Medicine and
Dentistry, Music, Dance and Drama, and Sociology. In all of these disciplines, Asian
students, particularly Chinese students, secured a higher percentage of upper degrees
than other BME students.
vi. Disability status was linked to attainment. Overall, 66% of students reporting a disability
attained an upper degree, whereas, for instance, 63% of students with a specific learning
disability (by far the largest group of disabled students) attained an upper degree. In all
10
vii.
viii.
ix.
x.
but three disciplines – Business and Management, Economics, and Finance and
Accounting – students reporting a disability were less likely to achieve an upper degree.
Mode of study was also linked to students’ achievement of an upper degree. Overall,
66% of full-time students achieved an upper degree as against 52% of part-time students.
With the exception of Built Environment, in all disciplines full-time students secured
higher percentages of upper degrees than did part-time students. In some disciplines the
attainment gap was stark. In Economics, Finance and Accounting, Marketing, Music,
Dance and Drama, and Politics, the attainment lead full-time students had over parttime students was 30% or higher.
Sixty-four per cent of EU students and 67% of UK students achieved an upper degree.
While EU students secured higher percentages of them in around half of the disciplines,
UK students achieved higher percentages in the other half. Only 49% of non-EU
students achieved an upper degree overall, however, and the gap between this group of
students and EU and UK students was considerable in some disciplines – for example,
English.
The distance between a student’s pre-HE address and their HEI was related to different
attainment rates. Sector-wide, students who travelled further afield to their HEI (70%)
were considerably more likely to attain an upper degree than students who travelled
less than 30 miles (61%). In 29/30 disciplines, students travelling to a more local
university achieved a lower percentage of upper degrees as compared to students
attending an institution further afield.
Finally, students’ degree attainment varied according to the nation in which they
studied. Overall 69% of students studying in Scottish and Northern Irish universities
achieved an upper degree, against 64% of students studying in English universities and
61% of students studying at Welsh universities who achieved one. Students attending
Scottish universities achieved the highest percentages of upper degrees in 15/30
disciplines.
11
Undergraduate retention and attainment across the disciplines
The report comprises two sections. Section one summarises information relating to differences in
key background characteristics of students from different HE disciplines, as well as characteristics
associated with their study. Section two summarises the report’s findings in relation to students’
retention and attainment patterns.
Throughout the report, the presented analysis is based upon at least 99.5%7 of the sample unless
otherwise stated. Where a considerable amount of cases had missing data – such as in relation to
the following measures: socio-economic class; parental HE qualifications; distance between pre-HE
address and HEI; and UCAS points – the missing data group has been included in the analyses and
findings (in the tables and corresponding text).
Section one – student characteristics by disciplinary area
The student body is not split evenly across the sector’s disciplinary areas (Table 1). Some
disciplines account for less than 1% of all students (Marketing, Philosophy and Religious Studies,
Politics, and Veterinary Medicine) whereas others account for over 5% of the sample (Art and
Design, Business and Management, Education, Engineering, Health, Nursing, and Other). As this
report will highlight, there are other important differences, in terms of student background, study
characteristics and outcomes, which are linked to disciplinary areas.
Variations between disciplines in terms of retention and attainment in section two of this report
should be understood in the context of variations in the background and on-course characteristics
of the student body.
7
99.5% rather than 100% as a small amount of cases had missing data in some instances of analysis.
12
Table 1: Introductory breakdown of student body by disciplines
Discipline
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport and
Tourism
Languages
Law
Marketing
Maths and Statistics8
Media and Communications
Medicine and Dentistry
Music, Dance and Drama
Nursing
Other9
Philosophical and Religious Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
Total
% of student body in the
discipline
5.8
3.2
2.7
7.5
4.2
1.2
6.4
6.5
2.7
2.0
2.0
5.1
3.1
No of students in
the discipline
95,070
52,917
44,546
122,607
67,847
20,317
103,881
106,169
44,219
32,771
32,814
83,073
49,889
3.7
60,804
1.9
3.8
0.8
1.6
1.9
2.0
2.6
9.4
6.3
0.9
2.1
0.9
3.7
3.3
2.0
0.6
100.0
31,736
61,880
13,162
25,805
30,642
32,517
43,183
153,962
103,254
14,186
34,633
14,906
59,582
53,615
32,346
9,135
1,631,468
8
The full title of this discipline area is: Maths and Statistics and Operational Research but is referred to throughout
this report as ‘Maths and Statistics’.
9
Seventy-three per cent of students taking a degree in the disciplines labelled ‘Other’ (a ‘Combined’ degree
programme) do so through the Open University.
13
1.1 Socio-demographic characteristics of students
Age
‘Traditional’10 age students comprised 60% of the sector as a whole (Table 2). With the exception
of Philosophy and Religious Studies, the balance between traditional and mature students in all
individual disciplines differed from the balance observed across the sector as a whole. The
strongest differences were observable in Economics, Politics, Physical Science, Music, Dance and
Drama, Medicine and Dentistry, Media and Communications, Marketing, and Hospitality, Sport,
Leisure and Tourism, where traditional-age students dominated, and Education, Nursing, Other,
and Social Work and Policy, where mature students dominated.
10
‘Traditional’ age is defined as under 21 at the start of a student’s degree, ‘mature’ is defined as over 21 at the start
of the student’s degree.
14
Table 2: Age11 distribution of students (traditional/mature) by discipline
Discipline
Sector as a whole
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport
and Tourism
Languages
Law
Marketing
Maths and Statistics
Media and Communications
Medicine and Dentistry
Music, Dance and Drama
Nursing
Other12
Philosophical and Religious
Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
No. of
% of
students who
students
were
who were
‘mature’ age
‘mature’ age
40
% of students
who were
‘traditional’
age
No. of
students who
were
‘traditional’
age
60
22
23
34
40
32
8
62
27
32
35
22
43
35
20,6654
12,043
15,047
48,428
21,590
1,681
64,644
28,315
13,964
11,459
7,246
35,708
17,622
79
77
66
61
68
92
38
73
68
65
78
57
65
74,398
40,717
29,493
74,131
46,253
18,636
39,197
77,848
30,247
21,307
25,566
47,352
32,253
16
9,772
84
51,030
49
29
18
25
15
20
15
76
83
15,412
17,716
2,402
6,523
4,627
6,390
6,257
117,315
85,728
51
71
82
75
85
80
86
24
17
16,212
44,163
10,759
19,279
26,014
26,127
36,924
36,593
17,252
41
5,810
59
8,364
17
18
36
72
33
29
5,995
2,688
21,307
38,984
10,757
2,626
83
82
64
28
67
71
28,635
12,218
38,272
14,619
21,586
6,465
11
Please note that 846 students had no age information, totalling < 1% of the sample. These have been excluded from
all age-related analyses here and elsewhere in this report.
12
Seventy-three per cent of students taking a degree in the disciplines labelled ‘Other’ (a ‘Combined’ degree
programme) do so through the Open University.
15
Traditional and mature students differed in relation to key background characteristics and in
relation to factors associated with their study (Table 3). For example, although women were overrepresented within the traditional age category of students, they were even more so in the mature
student category. Although there is a substantial amount of missing data in relation to social class
measures (socio-economic classification and parental HE – for further detail, see ‘socio-economic
classification’ below), mature students were less likely than younger students to report themselves
to be the higher socio-economic classes one and two13 and more likely to report as from socioeconomic classes three to nine, were also less likely than younger students to report that a parent
had an HE qualification. Mature students were also slightly more likely to identify as from a ‘White’
ethnic group, have less than 340 UCAS points (although note the missing data in relation to this
measure also), and attend a university closer to their pre-HE address. Mature students more often
studied part-time than full-time, whereas the reverse was true with traditional age students.
Mature students were also slightly more likely to study in England than elsewhere in the UK, and
were more likely to be domiciled in the UK (92%) before commencing their HE studies than
traditional aged students (88%).
13
1 = Higher managerial and professional occupations; 2 = Lower managerial and professional occupations; 3 =
Intermediate occupations; 4 = Small employers and own account workers; 5 = Lower supervisory and technical
occupations; 6 = Semi-routine occupations; 7 = Routine occupations; 8 = Never worked and long-term unemployed;
9 = Not classified.
16
Table 3: Background information on key demographic group - age
Student characteristics
‘Mature’ age
students
Gender
%/n who were men
37
%/n who were women
63
Socio-economic class (SEC)
%/n who were SEC1-2
8
%/n who were SEC 3-9
13
%/n with missing data
79
Parent HE
%/n who reported ‘Yes’
19
%/n who reported ‘No’
30
%/n with missing data
51
Ethnicity
%/n who were ‘White’
74
%/n who were BME
15
%/n with missing data
11
Mode of study
%/n studying full-time
34
%/n studying part-time
66
Country of domicile
%/n from non-EU country
5
%/n from EU country
3
%/n from UK
92
UCAS points
%/n with 340 or above
0
%/n with less than 340
10
%/n with missing data
90
Distance between pre-HEI domicile and HEI
%/n who travelled <30 miles
37
%/n who travelled >30 miles
20
%/n missing travel data
43
Nation of HEI
%/n studying in England
87
%/n studying in Northern Ireland
2
%/n studying in Scotland
6
%/n studying in Wales
5
No.
‘Traditional’
age students
No.
242,933
415,776
47
54
451,515
520,395
50,583
85,662
522,467
37
30
33
355,388
291,996
324,526
124,819
197,154
336,739
39
30
31
379,735
286,614
305,561
486,981
98,393
73,338
70
17
14
677,977
161,803
132,130
226,632
432,080
92
8
898,010
73,900
33,649
17,531
607,532
8
5
88
75,392
45,870
850,648
2,193
63,011
593,508
12
17
71
117,010
168,359
685,541
243130
129898
285684
26
53
21
252634
513097
206179
571,860
11,428
42,299
33,125
83
2
9
6
802,441
21,785
91,026
56,658
17
Gender
Women comprised the majority (57%) of students across the sector as a whole (Table 4). With
the exception of Marketing and Medicine and Dentistry, which mirrored this sector-wide gender
balance, in all other disciplines the gender balance differed from the sector average and confirmed
a pattern of gendered educational segregation in many areas of HE. The most male-dominated
disciplines were Economics, Computer Science, Built Environment, and Engineering. The most
female-dominated were Education, Nursing, Psychology, Social Work and Policy and Veterinary
Medicine.
18
Table 4: Gender14 distribution of students by discipline
Discipline
Sector as a whole
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport
and Tourism
Languages
Law
Marketing
Maths and Statistics
Media and Communications
Medicine and Dentistry
Music, Dance and Drama
Nursing
Other
Philosophical and Religious
Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
No. of
% of students
students who
who were men were men
% of students
who were
women
No. of students
who were
women
60,913
29,845
12,946
59,144
11,249
6,390
83,572
14,618
30,975
15,639
15,208
59,466
26,993
43
36
43
71
52
83
69
20
86
30
52
54
28
46
34,517
23,072
31,600
63,463
56,598
13,927
20,308
91,551
13,244
17,132
17,606
23,607
22,896
57
64
56
29
48
17
32
81
14
70
48
46
72
54
56
33,909
44
26,895
35
39
43
60
47
43
44
12
39
11,150
24,235
5,632
15,574
14,282
13,845
19,029
17,916
40,340
65
61
57
40
53
57
56
88
61
20,585
37,645
7,530
10,231
16,360
18,672
24,154
136,045
62,914
46
6,570
54
7,616
62
56
20
19
28
21
21,628
8,389
12,018
10,160
8,993
1,951
38
44
80
81
72
79
13,005
6,517
47,564
43,455
23,353
7,184
14
Three students who identified as of indeterminate gender were removed for the purposes of analysis and for
confidentiality reasons.
19
Men and women students differed in some respects in relation to their other background
characteristics and factors associated with their study (Table 5). As has already been observed,
women were more likely than men to belong to the ‘mature’ student category. They were also
slightly less likely to identify as belonging to a higher social class or report a parent with HE
qualifications, and as being from a BME background. They were more likely than men to study at
an HEI closer to their pre-university address, and to study part-time. Women (91%) were also
slightly more likely to be domiciled in the UK before commencing their studies than men (87%).
20
Table 5: Background information on key demographic group - gender
Student characteristics
Men
Age
%/n who were traditional age
65
%/n who were mature age
35
Socio-economic class (SEC)
%/n who were SEC1-2
27
%/n who were SEC 3-9
23
%/n with missing data
50
Parent HE
%/n who reported ‘Yes’
32
%/n who reported ‘No’
27
%/n with missing data
40
Ethnicity
%/n who were ‘White’
69
%/n who were BME
16
%/n with missing data
15
Mode of study
%/n studying full-time
73
%/n studying part-time
27
%/n from non-EU country
8
%/n from EU country
4
%/n from UK
87
UCAS points
%/n with 340 or above
8
%/n with less than 340
15
%/n with missing data
77
Distance between pre-HEI domicile and HEI
%/n who travelled <30 miles
27
%/n who travelled >30 miles
42
%/n missing travel data
32
Nation of HEI
%/n studying in England
84
%/n studying in Northern Ireland
2
%/n studying in Scotland
8
%/n studying in Wales
6
No.
Women
No.
451,515
242,933
57
44
520,395
415,779
187,357
160,545
346,880
23
23
54
218,627
217,117
500,939
224,241
190,271
280,270
30
31
39
280,368
293,548
362,767
478,938
113,085
102,759
73
16
11
686,599
147,167
102,917
507,154
187,628
57,873
29,546
607,363
66
34
6
4
91
617,510
319,173
51,184
33,868
851,631
53,112
106,855
159,967
7
13
80
66,091
125,574
181,665
185,232
290,619
218,931
33
38
29
310,821
352,707
273,155
584,324
13,405
55,909
41,144
84
2
8
5
790,728
19,812
77,444
48,699
21
Socio-economic classification
There were two measures of social class background in the data. The first measure identifies the
socio-economic classification of the student using an occupation-based system (see footnote 7
above)15.
Overall, 25% of students came from socio-economic classes one and two, while 23% came from
classes three to nine. The remaining 52% of students had missing data on this measure. Table six
includes detail relating to the group of students with missing socio-economic information;
notwithstanding this additional information, the socio-economic class information provided here
should be treated with caution.
The second measure of socio-economic background relates to whether or not students reported
having a parent with a higher education qualification (Table 7). Thirty-nine per cent of students had
missing data on this measure, and this group is represented in the table. Again, due to the large
amount of missing data, parental HE information should be treated with caution.
Looking at the sector overall, approximately half of students who reported on parental
educational status, confirmed that at least one parent had an HE qualification (31%), while the
remaining half reported that they did not (30%). Some disciplines varied from this overall sector
pattern, and it can be observed that there was a tendency for the older higher education
disciplines, for example GEES, Biological Sciences, Physical Science, Economics, Maths and
Statistics, Medicine and Dentistry, and Politics, etc., to have a larger percentage of students
reporting a parent with HE qualifications.
15
For applicants prior to 2008-09, this is the socio-economic background/occupation of students aged 21 and over at
the start of their course, or for students under 21 the socio-economic background of their parent, step-parent or
guardian who earns the most. For applicants for 2008-09 entry only, this is based on the socio-economic
background/occupation of the student if they are not in full-time education, or for students in full-time education, the
socio-economic background of their parent, step-parent or guardian.
22
Table 6: Socio-economic class of students by discipline
Discipline
Sector as a whole
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport
and Tourism
Languages
Law
Marketing
Maths and Statistics
Media and Communications
Medicine and Dentistry
Music, Dance and Drama
Nursing
Other
Philosophical and Religious
Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
No. of
students
from
SEC 3-9
% of
cohort
with
missing
SEC data
No. of
cohort with
missing SEC
data
29,946
17,259
12,323
25,212
15,132
7,151
17,175
28,105
13,425
6,113
13,252
22145
16,461
23
32
28
23
18
29
21
23
22
23
24
25
27
20
30,445
15,054
10,312
21,987
19,394
4,334
24,001
23,569
10,267
7,742
8,268
22454
10,019
52
37
39
49
62
49
44
60
51
46
58
34
46
47
34,679
20,604
21,911
75,408
33,321
8,832
62,705
54,495
20,527
18,919
11,294
38,474
23,409
33
20,039
35
21,293
32
19,472
25
28
35
33
34
52
34
14
2
7,774
17,005
4,654
8,413
10,295
16,985
14,795
21,762
1,785
13
25
29
24
33
21
28
22
1
4,236
15,396
3,854
6,059
9,995
6,704
12,179
34,451
1,376
62
48
35
44
34
27
38
64
97
19,726
29,479
4,654
11,333
10,352
8,828
16,209
97,749
100,093
36
5,055
21
2,916
44
6,215
38
36
27
15
27
32
13,089
5,292
16,006
7,827
8,566
2,944
28
21
25
23
28
26
9,608
3,064
15,123
12,049
9,137
2,376
35
44
48
63
45
42
11,936
6,550
28,453
33,739
14,643
3,815
% of
students
from SEC
1 or 2
No. of
students
from SEC 1
or 2
% of
students
from SEC
3-9
25
32
33
28
21
22
35
17
27
30
19
40
27
33
23
Table 7: Parental education of students by discipline
Discipline
Sector as a
whole
Art and Design
Biological
Sciences
Built
Environment
Business and
Management
Computer
Science
Economics
Education
Engineering
English
Finance and
Accounting
GEES
Health
History
Hospitality,
Leisure, Sport
and Tourism
Languages
Law
Marketing
Maths and
Statistics
Media and
Comms
Medicine and
Dentistry
Music, Dance
and Drama
Nursing
Other
Philosophical
and Religious
Studies
% of students
with parents
with HE
qualifications
No. of
students
with parents
with HE
qualifications
31
% of students
with parents
without HE
qualifications
No. of with
parents
without HE
qualifications
30
% of
students
with
missing
parental
education
data
No. of
students
with
missing
parental
education
data
39
36
34,374
29
27,997
34
32,699
39
20,369
29
15,499
32
17,049
33
14,503
25
11,009
43
19,034
29
35,019
28
34,082
44
53,506
29
19,575
32
21,714
39
26,558
46
20
34
36
9,247
21,211
36,276
15,782
23
36
23
29
4,663
37,775
24,806
12,969
32
43
43
35
6,407
44,895
45,087
15,468
27
8,959
29
9,684
43
14,228
44
33
38
14,378
27,700
18,700
27
32
29
8,795
26,767
14,458
29
34
34
9,651
28,606
16,731
33
20,252
35
21,481
31
19,071
28
35
35
8,866
21,542
4,561
18
32
30
5,745
19,528
3,985
54
34
35
17,125
20,810
4,616
39
9,932
30
7,689
32
8,184
35
10,775
32
9,895
33
9,972
45
14,704
15
4,903
40
12,910
43
18,688
26
11,416
30
13,079
22
15
34,285
15,047
35
22
54,088
22,645
43
64
65,489
65,562
38
5,360
28
3,908
35
4,918
24
Physical Science
Politics
Psychology
Social Work and
Policy
Sociology
Veterinary
Medicine
39
45
33
13,368
6,717
19,929
28
24
34
9,820
3,544
20,315
33
31
33
11,445
4,645
19,338
21
11,227
39
20,945
40
21,443
31
10,118
36
11,497
33
10,731
33
3,045
25
2,308
41
3,782
Taking the social class measure with more available data, some notable differences between
students reporting a parent with HE qualifications and others are observable (Table 8). Students in
this group were unsurprisingly more likely to be classified as coming from socio-economic classes
one and two. A larger percentage of them were of traditional age, as compared to students
reporting no parental HE qualifications, and students with missing data. They were more likely to
possess 340 UCAS points, be studying full-time, and to be studying at an HEI that was more than
30 miles away from their pre-university address. Students with a parent with an HE qualification
(89%) were also more likely to be domiciled outside of the UK before their studies commenced
than students without such a parent (96%) and those with missing data on this issue (85%).
25
Table 8: Background information on key demographic group – students with a parent with an
HE qualification
A
parent
Student characteristics
with
Age
HE
No.
%/n who were traditional age
75
379,735
%/n who were mature age
25
124,819
Gender
%/n who were men
44
224,241
%/n who were women
56
280,368
Socio-economic class (SEC)
%/n who were SEC1-2
43
218,200
%/n who were SEC 3-9
20
100,456
%/n with missing data
37
185,953
Ethnicity
%/n who were ‘White’
72
363,928
%/n who were BME
16
78,980
%/n with missing data
12
61,701
Mode of study
%/n studying full-time
84
425,329
%/n studying part-time
16
79,280
Country of domicile
%/n from non-EU country
7
34,372
%/n from EU country
4
22,416
%/n from UK
89
447,821
UCAS points
%/n with 340 or above
12
59,862
%/n with less than 340
14
72,676
%/n with missing data
74
372,071
Distance between pre-HEI domicile and HEI
%/n who travelled <30 miles
25
125,201
%/n who travelled >30 miles
51
257,068
%/n missing travel data
24
122,340
Nation of HEI
%/n studying in England
85
427,938
%/n studying in N. Ireland
1
6,071
%/n studying in Scotland
10
51,585
%/n studying in Wales
4
19,015
No
parent
with HE
59
41
No.
286,614
197,154
Not
known
48
52
No.
305,561
336,739
39
61
190,271
293,548
44
56
280,270
362,767
19
36
46
90,451
172,966
220,403
15
16
69
97,334
104,240
441,465
77
18
6
371,855
85,399
26,566
67
15
18
429,757
95,873
117,409
72
28
349,540
134,280
54
46
349,796
293,243
3
2
96
12,784
8,825
462,211
10
5
85
61,901
32,173
548,965
7
16
77
34,272
76,919
372,629
4
13
83
25,069
82,835
535,135
36
40
24
175,266
193,074
115,480
30
30
40
195,588
193,184
254,267
88
1
8
3
427,282
4,695
39,225
12,618
81
4
7
9
519,834
22,452
42,543
58,210
26
Ethnicity
There was a considerable amount of missing data on reported ethnicity (Table 9), although the
degree to which this is the case varied across disciplines, and ranged from no missing ethnicity
reporting in the case of Veterinary Medicine through to 29% of missing information in the cases of
Economics and Finance and Accounting. In several disciplines Black and minority ethnic (BME)
students were notably over-represented as compared to their presence in the sector overall, and
their presence within other disciplines; examples of disciplines where this was the case include
both Economics (26%) and Finance and Accounting (29%) as well as Computer Science (25%),
Business and Management (19%), Law (29%), Marketing (20%), Social Work and Policy (21%),
Medicine and Dentistry (29%) and Health (27%). Conversely, in several disciplines, BME students
were notably under-represented; including English (9%), GEES (4%), Languages (10%), Music,
Dance and Drama (8%), Philosophy and Religious Studies (7%), History (6%), Other (9%) and,
most strongly in Veterinary Medicine, where, with 100% of students reporting, only 2% reported
themselves as coming from a BME background.
There were interesting variations across disciplines in terms of the particular ethnic origin of
participating BME students. For instance, while BME students within Business and Management
were fairly evenly split between those identifying as being ethnically ‘Black’ and those identifying as
being ethnically ‘Asian’, in other disciplines, such as Economics, Finance and Accounting, Health,
and Medicine and Dentistry there more students identifying as being from an ‘Asian’ background,
and Social Work and Policy had more students identifying as being from a ‘Black’ background.
27
% Asian or Asian British - Pakistani
Number
% Asian or Asian British - Bangladeshi
% Chinese
Number
% Other Asian
Number
Number
% White17
% Not known18
Number
0
0
0
0
0
0
0
0
0
0
0
0
0
0
241
121
112
454
259
46
274
220
69
114
42
251
28
3
2
3
3
4
4
8
2
3
1
6
1
7
1
1,487
1,542
1,268
4,411
2,894
1,658
1,640
2,775
605
1,826
297
5,685
497
2
1
3
2
2
4
3
2
2
1
5
0
5
1
683
1,502
732
2,883
2,414
555
1,856
1,858
524
1,690
97
3,849
252
1
0
1
1
1
2
1
1
1
1
2
0
1
0
415
458
207
1,367
988
275
932
579
248
555
58
775
125
1
1
1
1
1
1
2
0
1
0
2
0
1
0
972
365
397
1,041
741
410
194
1,000
122
545
113
741
128
1
1
2
1
1
3
2
1
2
1
3
0
3
0
883
1027
426
1627
1723
444
626
1908
222
845
115
2,093
179
3
4
3
3
3
4
4
2
3
3
3
2
3
3
4064
1766
1328
3772
2465
813
2332
3075
1,353
889
726
2,825
1,309
71
76
72
71
56
61
45
83
60
76
44
88
62
87
71785
38250
31652
68360
41524
9081
85755
64097
33663
14268
28979
51828
43313
13
12
11
15
25
15
29
6
25
15
29
6
11
7
11452
5621
6477
31162
10197
5945
6605
25960
6641
9505
1958
9495
3592
2
1,098
2
1,481
0
181
1
843
1
397
0
155
0
246
1
330
4
2,103
79
47954
10
6016
1
2
2
1
157
1291
310
165
1
6
5
2
301
3,661
629
584
0
1
0
0
55
292
56
34
1
5
4
5
276
2,888
501
1,172
1
6
2
2
149
3,524
257
486
0
2
1
1
55
1,076
79
269
1
1
1
2
246
357
111
508
1
2
1
2
220
948
116
509
4
4
4
3
1,192
2,675
547
815
75
56
62
72
23657
34844
8172
18512
17
17
18
11
5428
10324
2384
2751
Number
Number
1,590
1,886
1,367
5,523
3,616
940
1,906
3,940
377
2,137
325
4,538
256
% Other Ethnic16
% Asian or Asian British - Indian
4
2
4
3
5
5
5
2
4
1
7
1
6
1
Number
Number
1,498
379
580
2,007
1,026
150
1,761
757
395
397
104
993
210
Number
1
2
1
1
2
2
1
2
1
1
1
0
1
0
% Black or Black British – African
% Other Black British
Sector as a whole
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport
and Tourism
Languages
Law
Marketing
Maths and Statistics
Number
Discipline
% Black or Black British – Caribbean
Table 9: Ethnicity of students by discipline
16
Other (including mixed) includes: Mixed – White and Black Caribbean; Mixed – White and Black African; Mixed – White and Asian; Other mixed background; Other
ethnic background.
17
White includes: White; Irish Traveller.
18
Not known includes: Not known. Information refused. This category includes 11% of overseas students from whom ethnicity data is not collected.
28
Media and Communications
Medicine and Dentistry
Music, Dance and Drama
Nursing
Other
Philosophical and Religious
Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
2
0
2
2
1
684
111
846
2799
1206
4
2
1
8
2
1,130
655
563
11,820
1,605
0
0
0
0
0
113
27
134
633
273
2
10
1
2
1
611
3,343
236
2,873
1,386
1
5
0
1
1
254
1,468
55
971
1,082
1
1
0
0
0
151
301
33
391
357
1
2
0
0
1
168
652
98
392
496
1
4
0
2
1
201
1,272
171
3183
690
5
5
4
2
2
1387
1692
1857
3,362
2,326
72
59
82
77
86
22119
19266
35318
117879
88315
13
12
9
6
5
3824
3730
3872
9659
5508
1
130
2
240
0
23
1
142
1
150
0
45
0
50
1
92
3
469
82
11650
8
1195
1
1
2
4
2
0
212
100
1198
1940
772
12
2
4
3
7
5
0
579
577
1,708
3,478
1,546
9
0
0
0
1
1
0
45
50
182
316
152
1
3
2
3
2
2
0
885
272
1,537
921
725
37
2
1
2
2
2
0
622
199
1,113
1,051
730
5
1
1
1
1
2
0
202
144
451
368
534
7
1
0
1
0
0
0
356
25
286
71
110
14
1
1
1
1
1
0
363
147
559
246
241
14
3
4
4
3
4
2
1,134
646
2,415
1,710
1,367
159
77
64
77
78
73
87
26542
9593
45611
41881
23741
7931
11
21
8
3
8
10
3693
3153
4522
1633
2428
946
Looking overall and broadly at students’ ethnicity, some differences are observable between the groups ‘BME’, ‘White’ and ‘Unknown’ (Table 10).
Those students broadly classified as BME were more likely than those classified as White to be of traditional age, to be male, and to be classified
as coming from socio-economic classes three to nine. They were also more likely to study full-time, to study at an HEI within 30 miles of their
pre-university address and to study in England.
29
Table 10: Background information on key demographic group – ethnicity19
Student characteristics
BME
No.
Age
%/n who were traditional age
62
161,803
%/n who were mature age
38
98,393
Gender
%/n who were men
44
113,085
%/n who were women
57
147,167
Socio-economic class (SEC)
%/n who were SEC1-2
23
59,712
%/n who were SEC 3-9
30
77,199
%/n with missing data
47
123,341
Parent HE
%/n who reported ‘Yes’
30
78,980
%/n who reported ‘No’
33
85,399
%/n with missing data
37
95873
Mode of study
%/n studying full-time
75
196,181
%/n studying part-time
25
6,4071
UCAS points
%/n with 340 or above
7
17,182
%/n with less than 340
17
43,099
%/n with missing data
77
199,971
Distance between pre-HEI domicile and HEI
%/n who travelled <30 miles
53
136,668
%/n who travelled >30 miles
34
88,813
%/n missing travel data
13
34,771
Nation of HEI
%/n studying in England
95
247,895
%/n studying in N. Ireland
0
442
%/n studying in Scotland
3
6,729
%/n studying in Wales
2
5,186
White
No.
Unknown
No.
58
42
677,977
486,981
64
36
132,130
73,338
41
59
478,938
686,599
50
50
102,759
102,917
29
25
46
335,051
292,094
538,395
6
4
91
11,222
8,369
186,085
31
32
37
363,928
371,855
429,757
30
13
57
61,701
26,566
117,409
66
34
766,583
398,957
79
21
161,901
43,775
8
14
78
93,521
166,588
905,431
4
11
85
8,500
22,743
174,433
30
47
23
347,333
545,061
273,146
6
5
90
12,054
9,452
184,170
82
2
9
6
957,865
27,894
107,192
72,589
82
2
9
6
169,294
4,882
19,432
12,068
19
Please note that information against the ‘country of domicile’ measure is not included here as no ethnicity data are
available for students domiciled outside of the UK.
30
Disability20 status
In the sector as a whole, 9% of students reported themselves as having a disability while the
remaining 91% did not report one. Two disciplines had notably higher percentages of students
reporting disabilities: Art and Design and Music, Dance and Drama. In both cases, the higher
percentages were largely accounted for by students reporting a specific learning disability such as
dyslexia; 11% of Art and Design students reported themselves as having a specific learning
disability as did 9% of Music, Dance and Drama students. Eight per cent of Veterinary Medicine
students also reported themselves to have a specific learning disability. Generally speaking,
students reporting a specific learning disability accounted for the largest percentage of students
reporting a disability in each discipline; the only discipline where this was not the case was Other.
Some other disabilities were over-represented within specific disciplines. For instance, in English
and Psychology 2% of students reported themselves as having mental health difficulties as against a
sector average of 1%, and in Computer Science, 1% of students reported themselves as having an
autistic spectrum disorder as against all other disciplines where students reporting an Autistic
Spectrum Disorder (ASD) failed to reach 0.5%. Finally, against a sector average of 2%, some
disciplines had higher percentages of students reporting either two or more impairments or
reporting a disability that was not listed in the categories offered to them: History (4%), Other
(6%), and Psychology (4%).
20
Note that there was no further information available relating to the background or academic characteristics of
students in association with their disability status.
31
Sector as a whole
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport and Tourism
Languages
Law
Marketing
Maths and Statistics
Media and Communications
Medicine and Dentistry
1
(22,353)
1 (1,102)
1(65,941)
1 (312)
1 (1,173)
1 (1,019)
1 (189)
1 (987)
1 (769)
1 (853)
1 (325)
1 (423)
1 (1,065)
2 (1,004)
1 (418)
1 (551)
1 (906)
1 (116)
1 (492)
1 (411)
1 (340)
% (n) Not known disability
4
(82,859)
11(10,486)
5 (3,214)
6 (2,653)
3 (4,073)
4 (3,122)
3 (867)
4 (3,955)
4 (4,962)
2 (1,460)
2 (723)
6 (2,358)
5 (4,204)
4 (2,495)
5 (3,673)
1 (811)
2 (1,730)
4 (679)
2 (845)
5 (2,025)
4 (1,928)
% (n) A disability not listed
0
(3,052)
0 (278)
0 (123)
0 (38)
0 (95)
1 (497)
0 (21)
0 (43)
0 (217)
0 (125)
0 (43)
0 (67)
0 (70)
0 (169)
0 (41)
0 (80)
0 (64)
0 (12)
0 (146)
0 (134)
0 (9)
% (n) Specific learning disability
1
(15,079)
1 (868)
1 (618)
0 (130)
0 (532)
1 (703)
0 (71)
0 (496)
0 (410)
1 (607)
0 (114)
1 (318)
1 (489)
2 (955)
0 (154)
1 (366)
1 (583)
0 (25)
1 (282)
0 (190)
0 (95)
% (n) Autistic Spectrum Disorder
1
(18,522)
1 (1,255)
1 (723)
1 (486)
1 (956)
1 (788)
1 (224)
1 (1,138)
1 (798)
1 (684)
1 (294)
1 (331)
1 (1,247)
1 (598)
1 (556)
1 (478)
1 (766)
1 (141)
1 (264)
1 (499)
1 (375)
% (n) Two or more impairments
1
(14,335)
1 (1,236)
1 (647)
0 (200)
0 (486)
1 (635)
0 (115)
0 (438)
0 (442)
2 (1,019)
0 (132)
1 (261)
1 (657)
1 (627)
0 (198)
1 (496)
1 (570)
0 (75)
1 (265)
1 (405)
0 (152)
% (n) Unseen disability/chronic illness
0
(24)
0 (0)
0 (1)
0 (3)
0 (0)
0 (2)
0 (0)
0 (1)
0 (1)
0 (1)
0 (0)
0 (0)
0 (3)
0 (1)
0 (2)
0 (1)
0 (0)
0 (0)
0 (1)
0 (0)
0 (1)
% (n) Mental health difficulties
0
(5,269)
0 (312)
0 (177)
0 (105)
0 (286)
0 (311)
0 (38)
0 (399)
0 (185)
0 (224)
0 (71)
0 (70)
0 (286)
0 (208)
0 (97)
0 (195)
0 (279)
0 (27)
0 (73)
0 (152)
0 (51)
% (n) Personal care support
0
(5,236)
0 (345)
0 (176)
0 (124)
0 (241)
0 (227)
0 (46)
0 (438)
0 (179)
0 (194)
0 (66)
0 (93)
0 (312)
0 (188)
0 (145)
0 (222)
0 (158)
0 (21)
0 (65)
0 (96)
0 (104)
% (n) Wheelchair user/mobility difficulties
0
(2,859)
0 (106)
0 (80)
0 (46)
0 (166)
0 (195)
0 (41)
0 (168)
0 (134)
0 (107)
0 (54)
0 (49)
0 (170)
0 (112)
0 (69)
0 (81)
0 (148)
0 (13)
0 (67)
0 (55)
0 (52)
% (n) Deaf/hearing impaired
Discipline
% (n) Blind/partially sighted
Table 11: Disability status of students by discipline
91
(1,745,056)
84 (82,498)
90 (59,361)
91 (42,610)
95 (139,086)
91 (71837)
95 (29,537)
92 (98,491)
93 (108,783)
92 (59,078)
96 (43,212)
89 (33,552)
91 (84,065)
89 (50,326)
92 (63,211)
93 (50,790)
93 (66,130)
93 (15,442)
94 (37,382)
91 (40,158)
93 (43,263)
32
Music, Dance and Drama
Nursing
Other
Philosophical and Religious Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
0 (96)
0 (122)
0 (162)
0 (45)
0 (70)
0 (66)
0 (158)
0 (133)
0 (70)
0 (14)
0 (138)
0 (543)
0 (257)
0 (80)
0 (80)
0 (69)
0 (165)
0 (285)
0 (127)
0 (42)
0 (121)
0 (174)
0 (297)
1 (123)
0 (121)
0 (105)
0 (303)
0 (258)
0 (193)
0 (29)
0 (1)
0 (0)
0 (0)
0 (0)
0 (0)
0 (0)
0 (2)
0 (1)
0 (2)
0 (0)
1 (467)
0 (653)
1 (896)
1 (25)
1 (356)
1 (323)
2 (1,211)
1 (444)
1 (599)
1 (79)
1 (694)
1 (1,614)
0 (459)
2 (283)
1 (432)
1 (319)
1 (768)
1 (693)
1 (529)
1 (127)
1 (284)
0 (301)
3 (3,111)
1 (145)
1 (351)
1 (249)
2 (1,232)
1 (809)
1 (546)
0 (45)
0 (157)
0 (66)
0 (78)
0 (49)
0 (194)
0 (85)
0 (58)
0 (30)
0 (40)
0 (22)
9 (4,028)
5 (7,512)
1 (1,230)
6 (939)
4 (1,929)
5 (1,552)
4 (2,766)
6 (3,423)
5 (2,122)
8 (795)
1 (525)
1 (1,073)
3 (3,299)
1 (222)
1 (442)
1 (409)
2 (1,418)
2 (984)
1 (595)
1 (120)
86 (40,588)
92 (143,978)
91 (93,689)
87 (14,618)
91 (39,654)
90 (29,256)
89 (66,350)
88 (50,141)
89 (39,918)
88 (9,052)
1.2 Characteristics associated with students’ study
Mode of study
Taking the sector as a whole, students registered for full-time study comprised 69% of the sample. The balance between full-time and part-time21
students in all disciplines differed considerably from that observable in the sector as a whole, with wide variations between, for example, Medicine
and Dentistry on the one hand, where 99% of students were full-time, through to Other, where only 4% of students were full-time (Table 12).
Disciplines with heavy concentrations of full-time students included: Art and Design (93%), Economics (94%), Hospitality, Leisure, Sport and
Tourism (91%), Marketing (89%), Media and Communications (93%) and Music, Dance and Drama (96%). Disciplines with heavier concentrations
of part-time students included Education (53%), Languages (56%), and Social Work and Policy (51%).
21
Students at the Open University represent 35% of the part-time sample.
33
Table 12: Study mode of students by discipline
Discipline
% studying
full-time
Number
% studying
part-time
Number
Sector as a whole
69
31
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport
and Tourism
Languages
Law
Marketing
Maths and Statistics
Media and Communications
Medicine and Dentistry
Music, Dance and Drama
Nursing
Other
Philosophical and Religious
Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
93
85
71
66
80
94
47
80
73
73
82
75
68
88,247
44,843
31,533
81,023
54,052
19,105
48,577
84,566
32,312
23,840
26,770
62,040
33,798
7
15
29
34
20
6
53
20
27
27
18
25
32
6,828
8,074
13,013
41,584
13,795
1,212
55,304
21,603
11,907
8,931
6,044
21,033
1,6091
91
55,399
9
5,405
44
80
89
77
93
99
96
55
4
14,026
49,564
11,766
19,874
28,449
32,154
41,363
84,377
3,950
56
20
11
23
7
1
4
45
96
17,710
12,316
1,396
5,931
2,193
363
1,820
69,585
99,304
67
9,560
33
4,626
88
87
70
49
76
82
30,482
13,028
41,594
26,407
24,474
7,492
12
13
30
51
24
18
4,151
1,878
17,988
27,208
7,872
1,643
Pre-HE domicile
Overall 89% of students were domiciled in the UK before starting their higher education courses,
while 4% were domiciled in other areas of the EU and the remaining 7% were domiciled in non-EU
countries. In several disciplines, students from outside of the UK were over-presented as
compared to their presence in the sector overall, most notably in Economics (28%), Business and
Management (23%), Engineering (23%) and Finance and Accounting (27%). By contrast, students
from the UK were most notably over-represented in Education (3%), Other (3%), and Social
Work and Policy (2%).
34
Table 13: Pre-university area of domicile of students by discipline
Discipline
% EU
Number
% NonEU
Number
7
% UK
Number
Sector as a whole
4
89
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport
and Tourism
Languages
Law
Marketing
Maths and Statistics
Media and Communications
Medicine and Dentistry
Music, Dance and Drama
Nursing
Other
Philosophical and Religious
Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
5
5
6
8
5
7
1
6
3
7
2
5
2
4,510
2,437
2,616
9,224
3,348
1,436
960
6,723
1,263
2,224
701
3,703
888
6
5
7
16
8
21
1
17
11
20
3
5
3
5,716
2,385
3,159
19,252
5,442
4,297
1,429
17,589
4,728
6,479
848
4,300
1,672
89
91
87
77
87
72
98
77
87
73
95
90
95
84,844
48,095
38,771
94,131
59,057
14,584
101,492
81,857
38,228
24,068
31,265
75,070
47,329
5
2,713
4
2,434
92
55,657
7
5
7
3
6
2
4
1
1
2,142
3,091
925
769
1,684
778
1,913
1,620
896
7
10
10
6
6
7
3
3
2
2,196
6,187
1,289
1,569
1,816
2,369
1,371
3,944
1,608
86
85
83
91
89
90
92
96
98
27,398
52,602
10,948
23,467
27,142
29,370
39,899
148,398
100,750
3
476
2
346
94
13,364
4
10
4
1
2
2
1,439
1,490
2,130
370
761
184
4
9
3
1
4
7
1,525
1,373
1,580
420
1,125
609
91
81
94
99
94
91
31,669
12,043
55,872
52,825
30,460
8,342
35
UCAS points of students
There was a large amount of missing data against the UCAS points measure – 78% across the
sector as a whole, but in some disciplines, including Nursing and Other, data was missing in 89% of
cases. Although it is difficult to draw conclusions in this context, it can be observed from the
results presented in table 14 that there was a tendency again for the older academic disciplines,
for example GEES, Biological Sciences, Physical Science, Economics, History, Maths and Statistics,
Medicine and Dentistry, and Politics, etc., to have a larger percentage of students with 340 UCAS
points or above, while newer disciplines such as Business and Management, Built Environment,
Computer Science, Finance and Accounting, Marketing, Social Work and Policy, Hospitality, Sport,
Leisure and Tourism, etc., had smaller percentages of students with 340 UCAS points or above.
Although the disciplines of Nursing and Other had the most missing data on this measure, it is also
notable that they each only reported 1% of students with 340 UCAS points or above, while Social
Work and Policy reported only 2%.
36
Table 14: UCAS points of students by discipline
Discipline
% of
students
with 340
UCAS
points or
above
Number
% of
students
with less
than 340
UCAS
points
Number
14
% of
students
where
UCAS
data is
missing
Number
Sector as a whole
7
78
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport
and Tourism
Languages
Law
Marketing
Maths and Statistics
Media and Communications
Medicine and Dentistry
Music, Dance and Drama
Nursing
Other
Philosophical and Religious
Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
6
13
6
5
5
19
3
9
12
6
15
9
13
6,038
6,692
2,634
5,869
3,266
3,772
3,169
9,287
5,284
2,096
4,871
7,331
6,568
19
16
14
16
20
9
17
15
13
14
12
10
10
18,407
8,210
6,336
19,376
13,525
1,902
16,314
15,465
5,692
4,415
3,975
8,574
5,080
74
72
80
80
75
72
81
77
75
80
73
81
77
70,625
38,015
35,576
97,362
51,056
14,643
84,398
81,417
33,243
26,260
23,968
67,168
38,241
6
3,668
24
14,429
70
42,707
9
11
6
17
8
15
10
1
1
2,741
6,896
722
4,429
2,371
4,824
4,432
2,035
489
14
13
19
9
22
2
20
10
11
4,410
7,818
2,534
2,364
6,652
476
8,688
14,955
11,258
78
76
75
74
71
84
70
89
89
24,584
47,166
9,906
19,012
21,619
27,217
30,063
136,972
91,507
12
1,738
10
1,348
78
11,100
16
14
11
2
7
10
5,545
2,129
6,269
932
2,202
903
12
12
14
15
19
16
4,180
1,809
8,592
8,231
5,991
1,424
72
74
75
83
75
75
24,908
10,968
44,721
4,452
24,153
6,808
37
Distance travelled to university
There was a large amount of missing data against the ‘distance between pre-HE home and
university’ measure (Table 15). For the sector overall, 30% of cases had missing data, while 30%
reported that they were registered for their HE study at an institution 30 miles or less from their
pre-HE address, and the remaining 39% reported that they were registered for the HE study at an
institution that was more than 30 miles away from their pre-HE address.
Notwithstanding the missing data, we can see that some disciplines were more likely to have
students who travelled less than 30 miles to their HEI. These included: Education, Health,
Computer Science, Nursing, Social Work and Policy. Conversely, some disciplines were more
likely to have students who travelled further afield. These included: Economics, GEES, History,
Maths and Statistics, Philosophy and Religious Studies, Physical Science, Politics and Veterinary
Medicine. With some notable exceptions (e.g. Built Environment on the one hand, Health on the
other), it would seem that students who travelled further than 30 miles to their HEI were more
likely to study older academic disciplines (Economics, GEES, History, Maths and Statistics,
Philosophy and Religious Studies, Physical Science, Politics, and Veterinary Medicine), whereas
those who travelled less far were more likely to study in newer HE disciplines (e.g. Finance and
Accounting, Health, Nursing, Sociology and Social Work and Policy). Part of this effect is the
increased likelihood of certain groups of students studying for degrees more closely allied to a
career path and studying locally22; these include BME students and mature students. Indeed, if we
examine further the example of Nursing, in which mature students were dominant, 62% of them
studied this discipline at a local HEI. Similarly, in the case of Health, where 27% of students
identified as BME, 52% of such students studied this discipline at a local HEI. There were also
evident linkages between a students’ socio-economic class and their decision to travel further
afield, so that while 26% of students reporting themselves to be from socio-economic classes one
and two attended an HEI less than 30 miles from their pre-HE home, 40% of students from classes
three to nine did so. Similarly, 25% of students reporting a parent with HE qualifications travelled
to an HEI close to home as against 36% of those reporting no parental HE qualifications.
22
The use of the term ‘local’ here is not unproblematic. It is clear that in cities an HEI that is 30 miles away might very
well not be the ‘local’ option in any meaningful sense, while in rural areas, an HEI that is 33 miles away may be the
nearest available option for HE study. It is also the case that some disciplines, such as Veterinary Medicine, that
account for less than 1% of the student body, may be taught only in HEIs a long distance away, limiting university
choice to those that are farther afield.
38
Table 15: Distance between pre-university address and HEI by discipline
Discipline
Sector as a whole
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport
and Tourism
Languages
Law
Marketing
Maths and Statistics
Media and Communications
Medicine and Dentistry
Music, Dance and Drama
Nursing
Other
Philosophical and Religious
Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
% of
students
where HEI
is 30 miles
or less
from preHEI
address
30
29
26
31
25
37
17
37
22
23
35
16
36
19
Number
% of
students
where HEI
is more
than 30
miles from
pre-HEI
address
27,634
13,711
13,925
30,755
25,082
3,426
38,516
24,221
10,095
11,569
5,224
30,167
9,392
39
51
53
43
31
31
52
29
40
46
26
62
43
50
28
17,173
29
33
30
21
29
23
22
59
15
% of
students
where
Number
mileage
data is ‘not
applicable’/
missing
Number
48,692
28,004
19,056
37,432
20,832
10,492
30,093
42,077
20,277
85,64
20,397
35,730
25,169
30
20
21
26
44
32
32
34
38
31
39
22
21
31
18,744
11,202
11,565
54,420
21,933
6,399
35,272
39,871
13,847
12,638
7,193
17,176
15,328
52
31,298
20
12,333
9,163
20,428
4,007
5,285
9,005
7,396
9,362
91,112
15,466
34
40
46
49
54
63
58
32
8
10,913
24,477
6,052
12,576
16,389
20,497
24,902
49,354
7,826
37
27
24
31
17
14
21
9
77
11,660
16,975
3,103
7,944
5,248
4,624
8,919
13,496
79,962
22
3,141
55
7,745
23
3,300
24
17
28
39
35
10
8,330
2,483
16,845
20,879
11,317
946
58
51
40
27
41
58
20,071
7,623
23,597
14,591
13,262
5,338
18
32
32
34
24
31
6,232
4,800
19,140
18,145
7,767
2,851
39
Nation of higher education institution
Eighty-four per cent of students in the UK studied within England, while 8% studied within
Scotland, 6% studied within Wales and the remaining 2% studied within Northern Ireland. The
distribution of students across disciplines did not fall evenly across all four nations, however. For
example, students within English HEIs accounted for 87% of those in Arts and Humanities
disciplines, despite comprising 84% of the student body overall; they were particularly overrepresented within Media and Communications and Music, Dance and Drama. English HEIs also
had disproportionate percentages of students studying some social science disciplines: Economics,
Law, and Marketing. Students studying within Scottish HEIs accounted for 10% of those in Health
and Social Care disciplines and STEM disciplines, despite comprising 8% of the whole sample;
indeed, students in Scottish HEIs accounted for 17% of all Medicine and Dentistry students, 16% of
all Veterinary Medicine students and 13% of all Biological Sciences students and 12% of all Physical
Science students. They were also notably over-represented within the discipline of Finance and
Accounting. Students studying in Welsh HEIs were over-represented in Education, where they
accounted for 9% of all students in this discipline. Students studying in Northern Ireland were
notably over-represented in the discipline of Finance and Accounting, comprising 7% of its
students.
40
82
83
84
77
84
86
82
82
78
82
82
80
83
89
81
86
84
85
90
81
76
Number
88
% of students
studying within
Northern Ireland
27,312
Number
89
5,421
3,224
2,587
1,916
2
1
1
1
1
1
1,083
559
418
298
5
1,427
1
314
2,194
6
2,404
1
421
1,301
7
1,055
2
240
% of students
studying within
Wales
82,818
37,890
43,496
27,550
8
6
6
6
7
6
84
87
87
86
87
87
Number
% of students
studying within
Scotland
Sector as a whole
Arts and Humanities
Art and Design
English
History
Languages
Media and
Communications
Music, Dance and Drama
Philosophical and Religious
Studies
Health and Social Care
Health
Medicine and Dentistry
Nursing
Social Work and Policy
Veterinary Medicine
STEM
Biological Sciences
Built Environment
Computer Science
Engineering
GEES
Maths and Statistics
Physical Science
Psychology
Social Sciences
Business and Management
Economics
Education
Finance and Accounting
Hospitality, Leisure, Sport
and Tourism
Law
Marketing
Politics
Sociology
Other
Number
Discipline
% of students
studying within
England
Table 16: Distribution of students by study in each discipline across four UK nations
5,748
2,546
3,388
1,972
6
6
6
7
5
6
5
1,589
38,164
5
11,590
9
104,215
18,375
84,563
24,836
10
9
17
10
6
16
10
13
10
9
11
8
6
12
7
7
7
5
6
12
84
50,856
87
87
84
84
91
53,598
11,427
12,495
27,260
93,772
69,383
24,893
128,757
46,294
7,529
41,255
36,308
55,802
85,165
27,264
23,036
28,127
51,024
8,914
1,077
5,932
3,863
4
4
6
4
6
2
6
7
5
6
7
7
3
6
5
6
5
3
9
6
8
4,826
7
5
9
9
5
4,274
693
1,286
2,823
5,544
7,758
5,610
15,278
3,214
1,422
7,021
4,575
6,101
11,456
2,751
1,653
4,149
4,395
6,265
647
9,028
1,900
2
3
0
2
2
0
2
1
4
3
2
2
1
1
2
3
3
1
4
7
7
4,221
2
901
5
5
6
5
4
2,891
673
853
1,561
3,915
2
3
2
2
0
1,117
369
272
702
23
3,171
2,011
6,359
3,040
184
3,891
2,064
3,847
7,257
2,159
848
2,023
3,001
2,761
3
3,568
1,067
0
750
1,599
2,097
2,291
640
268
334
1,162
3,213
218
4,358
2,172
41
Section two - retention and attainment across the disciplines
Retention
Taking the sector as a whole, 94% of students either continued with their studies or had
successfully completed their studies, while 6% did not continue. The ‘continuing’ group included
55% of students who had progressed into the next year of their studies, 28% of students who had
gained the award they initially registered for (or higher), and 11% of students who were still
registered for study but were classified as in a ‘dormant or writing up’ period. A sizeable portion
of these latter students were accounted for by those studying within Other, most notably at the
Open University where 51% of students fell into this category, and where students can opt to take
just one or several modules without intending to study for a full degree. Some further disciplines
also had levels of ‘dormant’ students 10% or above, however. These include Business and
Management, English, History, Languages, Nursing, Psychology, Social Work and Policy.
All disciplines had continuation rates of over 90%, with most having rates in line with the sector
average of 94% or higher. Disciplines with the highest continuation rates – of 97% of above –
included Economics, GEES, History, Medicine and Dentistry; it is perhaps notable that these are
again all older HE disciplines. Three disciplines had percentages of students continuing that were
notably lower than the sector average: Computer Science (91%), Hospitality, Sport, Leisure and
Tourism (92%), and Languages (92%). The overall category of ‘non-continuing’ students is
comprised of two sub-categories, ‘students gaining an award lower than the qualification originally
aimed for’ and ‘students leaving with no award’. Overall, 2% of students left their studies with a
lower award than that originally aimed for, while 4% did so with no award. The disciplines with the
highest percentages of students in the category of those leaving with no award included Art and
Design (6%), Computer Science (6%) and Languages (8%).
42
Table 17: Retention of students23 by discipline
Discipline
Sector as a whole
Art and Design
Biological Sciences
Built Environment
Business and
Management
Computer Science
Economics
Education
Engineering
English
Finance and
Accounting
GEES
Health
History
Hospitality, Leisure,
Sport and Tourism
Languages
Law
Marketing
Maths and Statistics
Media and
23
% of
students
continuing
with
studies
55
61
62
59
Number
% of
students
gaining
intended
award or
higher
58,582
32,868
26,319
28
29
27
30
50
61,312
59
65
46
63
56
Number
% of
students
dormant/
writing
up
27,137
14,406
13,239
11
4
5
5
33
39,883
38,672
13,139
46,581
66,365
24605
24
28
39
25
30
56
16,529
63
60
60
Number
% of
students
gaining
award
lower than
qualification
originally
aimed for
3,302
2,783
1,987
2
2
2
2
11
13,117
16,208
5,706
39,363
25,947
12907
8
4
9
6
10
32
9,444
20,800
49,417
29,813
27
29
26
60
36,490
42
61
62
64
61
13,361
37,208
7,688
16,381
18,628
Number
% of
students
leaving with
no reward
Number
% total
continuing
or
successfully
completing
studies
% total
students
gaining
lower or
no
award
6
6
5
6
2,007
1,016
984
4
6
3
4
4,029
1,785
1,967
94
94
94
94
2
2,483
4
5,161
94
6
5,697
865
9,183
6,371
4240
3
1
2
3
1
2,273
199
2,098
3,024
484
6
2
5
4
3
3,966
408
4,975
4,229
1360
91
97
94
94
96
9
3
7
7
4
7
1936
2
532
4
1,102
95
5
8,749
24,018
12,928
7
6
11
2,270
4,843
5,500
1
2
1
274
1,665
347
2
3
3
719
2,676
1,292
97
95
97
3
5
4
28
16,929
4
2,594
3
1,630
5
3,128
92
8
38
27
28
23
29
11,891
16,522
3,532
5,964
8,732
12
7
4
9
4
3,863
4,083
535
2,288
1,290
0
2
2
2
3
126
1,075
226
383
772
8
4
4
3
4
2,486
2,165
511
655
1,187
92
95
94
96
94
8
5
6
4
6
2% (n = 32,112) students have been removed from the sample for the purposes of this analyses as their registration status was unclear.
43
Communications
Medicine and Dentistry
Music, Dance and
Drama
Nursing
Other
Philosophical and
Religious Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
76
24,635
21
6,738
2
726
0
17
1
381
99
1
60
25,574
31
13,121
3
1,396
2
851
4
1,539
94
6
51
24
68,061
24,237
32
9
43,053
9,509
11
60
15,201
60,984
2
3
2,516
2,962
5
4
6,038
3,547
94
93
6
7
58
8,216
29
4,035
7
960
3
373
4
579
94
7
66
64
62
47
57
58
22,776
9,599
37,138
24,656
18,531
5,300
23
26
23
32
27
29
7,904
3,890
13,738
16,864
8,792
2,659
5
5
10
13
9
8
1,848
903
5,945
6,915
2,849
730
3
1
2
3
2
1
856
154
949
1,303
624
104
4
2
3
5
5
3
1,241
360
1,714
2,432
1,548
286
94
96
95
92
93
95
7
3
5
8
7
4
44
Tables 18 a-c provide further detail on the composition of students who continued or left with no
award or a lower award than the one they initially aimed to achieve. Looking at the sector overall,
there were small, but noteworthy, differences between the rate at which diverse groups of
students continued or completed their studies or left without an award. There were also notable
variations in continuation/non-continuation rates between difference groups of students across the
range of disciplines.
Overall, 7% of mature students and 5% of traditional age students left without their award. Larger
percentages of mature students than traditional age students left without their award in all
disciplines except Maths and Statistics, Nursing, Social Work and Policy and Veterinary Medicine.
Some disciplines had more substantial age gaps than others. At the top end were Law, Marketing,
Philosophy and Religious Studies, and Physical Science, where mature students were twice as likely
to leave without their award than their traditional age counterparts. As has been outlined in
section 1.1, mature students were less likely to be identified as from socio-economic classes one
and two and less likely to study full-time, and these intersecting characteristics are also related to
non-continuation. Overall part-time students (8%) were more likely than full-time students (5%) to
withdraw without their award. Indeed, in all disciplines except Maths and Statistics, Other,
Psychology, and Veterinary Medicine, part-time students were more likely than full-time students
to leave with no award or a lower than intended award. In some disciplines, the difference
between part-time and full-time students was larger than others. For example, in Marketing, 24%
of part-time students withdrew under this category as against 5% of full-time students who did; in
Languages 12% of part-time students withdrew against 3% of full-time students who did; in Music,
Dance and Drama 15% of part-time students withdrew against 5% of full-time who did; and in
Philosophy and Religious Studies 12% of part-time students withdrew as against 4% of full-time
students who did.
In terms of gender overall, 7% of men and 5% of women withdrew without their award. Larger
percentages of men withdrew with a lower or no award than women across all disciplines except
Other, where 6% of men were in this category as against 7% of women, and Physical Science and
Veterinary Medicine where the same percentages of men and women were in this category (6%
and 4% respectively). Some disciplines had more sizeable gender gaps than others. Those
disciplines with the largest gender gaps were Education, where 10% of men withdrew without
their award against 6% of women who did, and Hospitality, Leisure, Sport and Tourism, where 9%
of men withdrew as against 6% of women again. This finding is of particular interest as men were
not more likely than women to possess intersecting background characteristics that are linked to
non-continuation, for example as part-time and mature status.
For the sector as a whole, students from socio-economic classes one and two left without their
award least often (5%), while students from socio-economic classes three to nine were slightly
more likely to do this (6%) and students with missing data on this measure were 2% more likely to
do this (7%). In terms of disciplines, this pattern obtained across most; students identified as being
from socio-economic classes one and two were slightly (1% or 2%) less likely to withdraw than
students within the other two groups. Similarly, in terms of parental education, those students
who reported a parent with an HE qualification (5%) were slightly less likely overall to withdraw
with no award or a lower award than students who did not report a parent with HE qualifications
(6%) or who had missing data (7%) on this measure.
Students’ ethnic background was linked to varied continuation rates. Looking at the broad
difference between White and BME students across the sector overall, White (6%) students were
less likely than BME (8%) students to leave without their award. In terms of disciplinary
differences, BME students overall recorded lower levels of continuation in all disciplines than did
45
‘White’ students. There were important differences within the broad group of BME students,
however, so that, with few exceptions, ‘Chinese’ students recorded the lowest levels of noncontinuation across most disciplines, followed by ‘White’ students and students from ‘Asian or
Asian British – Indian’ background. Wide variations in non-completion rates across the full range
of disciplines emerged among most sub-groups of students from BME backgrounds as compared to
White students where non-completion rates in all 30 disciplines remained under 10% and was
comparatively stable across the sector. For instance, although there are similarly small numbers of
‘Black or Black British – Caribbean’ students in Philosophy and Religious Studies (n = 130) and
Maths and Statistics (n = 165), 24% of them withdraw without their award from the former
discipline while 3% do so from the latter.
Across the sector as a whole, students reporting a disability were no more likely (6%) than
students not reporting one (6%) to leave without their award. In some disciplines – Art and
Design, Computer Science, Economics, Engineering, Hospitality, Leisure, Sport and Tourism,
Languages, Psychology and Social Work and Policy – there were no differences in noncontinuation between students with a reported disability and those without. In others, however,
students with a disability were slightly (1% or 2%) more likely to leave without their award. In two
disciplines – Music, Dance and Drama, and Other – students with a disability were 1% less likely
than students without a reported disability to withdraw without their award.
Overall, 5% of students domiciled within the EU before commencing their studies withdrew
without their awards, while 6% of students domiciled outside of the EU and the UK did so. The
impact of country of domicile had a less uniform impact on students’ likelihood of withdrawing
from their studies across the disciplines. In some, such as Art and Design and Biological Sciences
there were no differences in non-continuation rates between students domiciled in the UK,
Europe or non-European countries. In other disciplines, for example Law, Maths and Statistics,
Veterinary Medicine, students from non-European countries, were less likely to leave their
courses than students domiciled in the UK before their studies. There were wide differences in
other disciplines between non-EU domiciled students and others, however, so that in Education
for instance, 33% of students from non-European countries left without their degree as against 7%
of students from EU countries and the UK.
In terms of the sector overall, students with 340 UCAS points or above (4%) were considerably
less likely than those with less points (9%) to leave their courses without their award. Six per cent
of students with missing data on this measure (the majority) withdrew without their award. In all
disciplines except for Other, students with 340 points withdrew less often. In 17/30 of the
individual disciplines, they withdrew at half the rate of their counterparts with less than 340 points.
Notwithstanding the context of missing data, overall, students who attend a university that was 30
miles or less away from their pre-HE address (8%) were more likely to withdraw without their
award than students who attend a university further afield (5%) or students with missing data on
this measure (5%). With the exception of two disciplines – Medicine and Dentistry and Social
Work and Policy – students who attend a university that was 30 miles or less away from their preHE address were more likely to withdraw without their award across all disciplines. The impact of
distance was more marked in certain disciplines such as Economics, Languages, Other, Sociology
and Veterinary Medicine. As has been seen in table 15 above, distance between pre-HE address
and university is related to other intersecting socio-demographic characteristics that show an
increased likelihood of non-continuation: mature student status, BME status and membership of a
lower socio-demographic class.
46
The nation of study was also related to varied continuation rates. Overall, Northern Ireland had
the lowest non-continuation rate of just 3%, followed by England and Scotland, with rates of 6%,
and finally, Wales, with a rate of 11%. Northern Ireland saw the lowest percentages of students
leaving without their award across most disciplines, except Economics (England), GEES (where it
shared the lowest rate with England), Languages (Scotland), Music, Dance and Drama (where it
shared the lowest rate with Scotland) and Politics (Scotland). Wales was the nation with the
highest percentages of students withdrawing without their award in most disciplines.
47
Table 18a: Art and Design – Finance and Accounting – leavers without degree by discipline, further detail
% left, lower or no
award
Art and
Design
Biological
Science
Built
Environment
Business and
Management
Computer
Science
Economics
Education
Engineering
English
Finance and
Accounting
Age
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
Traditional
Mature
6
7
4,515
1,519
5
7
1,907
892
6
8
1,813
1,137
5
8
3,992
3,650
9
10
4,112
2,127
3
8
468
139
6
8
2,300
4,767
6
9
4,751
2,501
4
5
1,118
724
5
8
980
654
7
6
2,436
3,600
6
5
1,414
1,387
7
6
2,156
795
7
5
4,493
3,151
10
8
5,347
892
3
2
463
144
10
6
1,988
5,085
7
5
6,563
690
6
4
730
1,114
6
5
995
639
5
7
7
1,534
1,974
2,528
4
6
6
665
839
1,297
5
7
7
670
716
1,565
5
6
7
1,197
1,385
5,062
8
10
9
1,204
1,890
3,145
2
3
4
129
135
343
4
5
8
745
1,186
5,142
5
7
7
1,513
1,715
4,025
3
4
5
353
416
1,075
4
6
6
239
425
970
5
7
7
1,867
1,955
2,214
4
6
6
890
903
1,008
6
7
7
798
792
1,361
5
7
7
1,804
2,224
3,616
8
10
10
1,569
2,076
2,594
2
3
4
223
156
228
6
6
9
1,218
2,159
3,696
6
7
8
2,030
1,792
3,431
3
4
6
514
510
820
5
6
6
380
546
708
Black or Black British
Caribbean
9
138
13
48
12
67
10
194
12
125
7
10
11
192
13
98
7
28
15
52
Black or Black British
African
13
199
10
191
12
157
9
501
13
458
6
59
23
433
10
387
10
37
7
137
Other Black background
10
25
11
13
11
12
10
46
14
35
11
5
22
59
12
26
10
7
14
15
Asian or Asian British Indian
7
104
6
90
9
109
5
236
9
261
2
31
6
103
7
180
4
21
8
141
Asian or Asian British Pakistani
9
63
7
97
11
83
9
257
11
268
6
32
7
128
10
186
5
25
8
120
Asian or Asian British Bangladeshi
8
31
5
23
14
28
8
111
11
112
4
11
8
78
12
66
4
9
7
36
Gender
Men
Women
Socio-economic class (SEC)
One and two
Other SEC
Unknown
Parent HE
Yes
No
Unknown
Ethnicity
48
Chinese
6
55
2
7
6
23
5
55
7
50
3
11
14
26
4
41
14
17
5
25
Other Asian background
9
79
7
68
13
55
8
127
13
221
2
10
13
82
8
159
5
10
9
68
Other ethnic
background
7
269
5
94
9
113
8
284
12
292
3
27
11
252
8
235
5
63
8
61
White
Unknown
6
7
4,330
743
5
5
1,874
296
6
6
1,938
366
6
6
3,895
1,938
8
10
3,441
976
3
3
232
179
6
13
4,858
862
7
6
4,332
1543
3
9
1,089
538
5
4
622
357
No known disability
6
5,351
5
3,086
6
2,754
6
8,475
9
6,315
3
859
7
6,599
7
7,307
4
2,343
5
1,955
Known disability
6
930
6
412
7
285
7
496
9
663
3
56
8
638
7
600
5
267
6
103
6
13
5,145
891
5
8
2,193
608
6
8
1,905
1,046
6
8
4,546
3,098
9
10
4,863
1,376
3
9
499
108
6
8
2,841
4,232
6
10
5,046
2,207
4
5
1,251
593
5
10
1,075
559
6
6
6
334
269
5,433
5
5
5
118
110
2,573
5
5
7
164
136
2,651
6
4
7
1,233
316
6,095
10
6
9
531
189
5,519
3
3
3
123
43
441
33
7
7
472
61
6,540
5
7
7
941
454
5,858
10
6
4
430
72
1,342
4
3
6
261
56
1,317
6
10
5
376
1,882
3,778
4
9
5
233
711
1,857
5
11
6
142
669
2,140
5
9
6
275
1,656
5,713
7
12
9
236
1,665
4,338
2
6
3
71
108
428
5
8
7
160
1,356
5,557
4
12
6
378
1,785
5,090
3
7
4
160
423
1,261
4
7
6
80
276
1,278
Disability
Mode of study
Full-time
Part-time
Country of domicile
Non-EU
EU
UK
UCAS points
Above 340 points
Below 340 points
Unknown
Distance between pre-HEI domicile and HEI
30 miles or less
Above 30 miles
Distance unknown
7
6
7
2,056
2,761
1,219
7
4
6
995
1,146
660
8
6
7
1,057
1,060
834
8
6
6
2,380
2,192
3,072
11
9
8
2,767
1,814
1,658
6
2
3
194
232
181
8
5
7
3,077
1,626
2,370
9
6
7
2,116
2,358
2,779
6
3
5
575
624
645
8
5
4
766
403
465
6
4
5
7
5,328
44
273
391
5
2
6
5
2,187
14
402
198
7
5
6
10
2,396
81
263
211
6
3
7
8
6,485
100
575
484
9
7
9
12
5,085
137
552
465
3
7
4
6
514
16
41
36
7
1
7
9
5,901
44
378
750
7
3
7
10
5,692
69
799
693
4
3
4
4
1,629
18
95
102
6
2
5
7
1,303
46
185
100
Nation of HEI
England
Northern Ireland
Scotland
Wales
49
Table 18b: GEES - Medicine and Dentistry - leavers without degree by discipline, further detail
% left, lower or no
award
GEES
Health
History
Hospitality,
Leisure, Sport
and Tourism
Language
Law
Marketing
Maths and
Stats
Media and
Communications
Medicine
and
Dentistry
Age
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
Traditional
Mature
3
4
680
313
4
7
1,871
2,469
3
4
914
723
8
9
3,849
909
6
10
1,005
1,595
4
8
1,823
1,417
5
11
538
199
4
4
764
274
6
8
1,568
390
1
2
263
135
4
3
618
375
6
5
1,340
3,001
4
3
803
836
9
6
3,097
1,661
9
8
1,038
1,574
6
5
1,511
1,729
7
5
381
356
5
3
696
342
7
6
1,025
934
2
1
213
185
2
3
4
297
272
424
4
5
7
844
1,019
2,478
2
4
4
388
357
894
7
8
9
1,323
1,696
1,739
5
7
10
369
278
1,965
4
5
7
608
747
1,885
6
5
7
242
199
296
4
4
4
325
254
459
6
7
7
575
649
735
1
1
2
160
88
150
2
4
4
339
319
335
4
5
6
1,162
1,411
1,766
2
4
4
441
516
682
7
8
8
1,351
1,798
1,609
6
8
10
531
441
1,640
4
6
6
951
1,079
1,210
5
6
7
206
242
289
4
4
4
372
332
334
6
7
7
602
646
711
1
2
1
196
98
104
5
5
11
109
7
15
12
134
8
12
10
120
9
26
3
5
11
72
5
5
7
23
8
360
7
18
11
167
16
48
8
278
8
45
8
44
11
123
2
12
7
3
9
23
7
2
15
27
9
5
12
33
13
7
-
-
12
14
-
-
3
8
4
225
3
15
10
86
10
30
5
127
8
37
4
43
6
38
1
43
9
9
6
213
4
10
13
52
16
24
7
232
7
18
5
24
11
29
2
26
5
3
5
42
4
5
17
26
9
5
7
74
17
13
5
12
6
9
1
4
5
6
4
31
2
2
5
12
15
36
4
15
6
7
4
22
3
5
1
6
Gender
Men
Women
Socio-economic class (SEC)
One and two
Other SEC
Unknown
Parent HE
Yes
No
Unknown
Ethnicity
Black or Black British
Caribbean
Black or Black British
African
Other Black
background
Asian or Asian British Indian
Asian or Asian British Pakistani
Asian or Asian British Bangladeshi
Chinese
50
Other Asian
background
Other ethnic
background
White
Unknown
7
8
6
118
3
5
10
34
10
21
7
61
9
10
6
30
7
14
2
19
4
27
6
160
4
55
10
205
9
107
7
187
8
40
6
48
8
117
1
17
3
4
818
83
5
5
2,589
471
3
6
1,309
203
8
7
3,581
434
7
13
1,624
700
5
5
1,628
485
6
5
419
115
4
5
676
134
6
5
1,356
182
1
2
204
62
No known disability
3
996
5
4,205
3
1,603
8
6,3179
7
3,390
5
3,333
6
854
4
1,343
6
2,487
1
471
Known disability
4
140
6
512
4
268
8
434
7
249
6
332
8
91
5
128
7
289
2
56
3
4
740
253
4
8
2,614
1,727
3
4
1,015
624
7
13
4,063
695
3
12
409
2,203
4
10
2,070
1,170
5
24
561
176
4
3
843
195
6
11
1,713
246
1
4
384
14
5
4
3
38
28
927
4
5
5
190
165
3,986
7
3
3
110
28
1,501
8
6
8
189
170
4,399
16
10
8
354
215
2,043
4
5
6
231
144
2,865
6
3
6
79
27
631
4
6
4
64
44
930
4
5
7
77
76
1,806
2
2
1
39
12
347
2
5
3
118
206
669
4
8
5
259
680
3,402
3
7
3
208
333
1,098
8
12
7
278
1,727
2,753
5
16
7
137
685
1,790
3
8
5
232
610
2,398
6
8
5
45
206
486
3
7
4
133
158
747
6
11
5
150
695
1,114
1
3
1
59
15
324
Disability
Mode of study
Full-time
Part-time
Country of domicile
Non-EU
EU
UK
UCAS points
Above 340 points
Below 340 points
Unknown
Distance between pre-HEI domicile and HEI
30 miles or less
Above 30 miles
Distance unknown
5
3
3
260
537
196
6
4
6
1,774
1,534
1,033
6
3
3
555
673
411
10
7
8
1,659
2,093
1,006
13
6
6
1,187
686
739
7
4
5
1,442
1,045
753
8
5
4
293
314
130
6
4
3
322
502
214
8
6
5
702
993
264
1
1
3
92
188
118
3
3
4
4
787
17
103
86
5
2
5
5
3,733
49
417
142
3
3
4
6
1,335
13
147
144
8
5
8
8
4,013
45
376
324
9
7
3
4
2,439
22
68
83
5
4
5
5
2,854
39
192
155
6
4
4
7
657
14
26
40
4
2
5
6
901
6
84
47
7
2
4
8
1,768
6
66
119
1
33
0
1
357
1
24
16
Nation of HEI
England
Northern Ireland
Scotland
Wales
51
Table 18c: Music, Dance and Drama – Veterinary Medicine - leavers without degree by discipline, further detail
% left, lower or no
award
Music,
Dance and
Drama
Nursing
Other
Philosophy
and Religious
Studies
Physical
Science
Politics
Psychology
Social Work
and Social
Policy
Sociology
Veterinary
Medicine
Age
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
Traditional
Mature
5
8
1,881
509
7
6
2,375
6,174
6
7
976
5,490
4
11
334
618
5
11
1,443
653
3
5
373
141
4
5
1,539
1,124
8
7
1,182
2,552
6
9
1,186
984
5
4
290
100
6
5
1,166
1,224
8
6
1,233
7,321
6
7
2,482
4,027
7
6
464
488
6
6
1,357
740
4
3
321
193
6
4
725
1,938
9
7
864
2,871
8
6
721
1,451
4
4
76
314
4
6
7
619
669
1,102
7
6
6
1,403
2,010
5,141
10
13
6
172
173
6,164
5
5
9
229
147
576
4
6
8
582
581
934
3
3
4
151
114
249
4
5
5
602
754
1,307
7
7
7
563
837
2,335
5
6
9
403
525
1,244
3
6
4
90
133
167
5
7
6
832
725
833
6
7
6
2,027
3,288
3,239
2
3
9
355
644
5,510
5
7
9
248
261
443
4
6
8
593
618
886
3
5
4
180
158
176
4
5
5
792
1,008
863
6
7
8
708
1,423
1,604
5
6
9
488
712
972
3
6
4
105
143
142
10
87
9
201
6
69
24
31
9
20
7
7
8
89
9
166
9
68
8
1
9
51
7
668
14
218
12
29
10
59
7
41
8
138
9
312
7
112
-
-
10
13
6
32
12
33
22
5
16
7
10
5
11
19
10
31
9
13
-
-
7
16
6
122
8
110
4
6
6
51
6
15
3
39
7
62
5
38
-
-
9
5
8
67
11
121
12
17
8
52
7
13
5
57
6
66
8
55
-
-
3
1
6
22
21
76
7
3
7
14
6
8
6
26
8
29
6
32
-
-
Gender
Men
Women
Socio-economic class (SEC)
One and two
Other SEC
Unknown
Parent HE
Yes
No
Unknown
Ethnicity
Black or Black British
Caribbean
Black or Black British
African
Other Black
background
Asian or Asian British Indian
Asian or Asian British Pakistani
Asian or Asian British Bangladeshi
52
Chinese
Other Asian
background
Other ethnic
background
White
Unknown
3
3
7
22
21
98
4
2
3
11
4
1
3
8
4
3
2
2
-
-
5
9
7
155
14
95
5
5
8
27
6
9
5
26
9
20
6
15
7
1
7
134
7
213
9
197
6
30
7
77
4
27
6
141
7
120
7
94
6
9
5
7
1,818
253
6
7
6,517
535
6
12
4,892
600
6
7
738
86
6
7
1,534
245
3
4
278
110
4
6
1,848
272
7
11
2,762
164
7
7
1,570
173
4
3
350
29
6
5
2,283
332
6
7
7,816
810
7
6
5,982
570
6
8
900
162
6
8
2,202
319
3
4
1,014
131
5
5
3,035
419
7
7
3,455
494
6
8
2,480
367
4
5
338
69
5
15
2,121
269
6
7
5,010
3,544
11
6
395
6,114
4
12
422
530
5
12
1,619
478
3
4
433
81
5
4
1,896
767
7
8
1,792
1,943
6
11
1,334
838
5
3
339
51
6
6
6
81
120
2,189
8
7
6
270
97
8,187
8
10
6
100
88
6,312
6
8
7
20
38
894
6
7
6
95
99
1,903
4
3
4
51
40
423
5
6
4
85
124
2,454
9
11
7
37
37
3,661
6
7
7
63
53
2,056
2
6
4
12
11
367
5
10
4
226
866
1,298
6
8
6
127
1,089
7,338
8
4
7
40
471
5,998
4
10
7
73
135
744
3
10
6
171
433
1,493
3
6
3
62
111
341
4
7
4
250
620
1,793
6
10
7
56
841
2,838
4
10
6
93
607
1,472
3
9
4
27
129
234
Disability
No known disability
Known disability
Mode of study
Full-time
Part-time
Country of domicile
Non-EU
EU
UK
UCAS points
Above 340 points
Below 340 points
Unknown
Distance between pre-HEI domicile and HEI
30 miles or less
Above 30 miles
Distance unknown
7
4
8
633
1,083
674
6
7
7
4,618
3,089
847
29
12
2
4,021
935
1,553
8
5
11
244
358
350
8
5
7
670
1,012
415
6
3
3
145
223
146
7
4
3
1,106
910
647
8
8
6
1,547
1,122
1,066
10
5
5
1,130
680
362
7
2
7
66
122
202
6
4
4
6
2,138
15
95
142
6
2
8
5
7,012
55
1,203
284
3
0
7
84
2,821
0
402
3,286
6
4
7
12
732
10
84
126
6
2
8
8
1,615
6
321
155
4
3
2
3
453
9
26
26
4
3
6
5
2,237
29
247
150
7
3
9
11
3,108
27
273
327
5
3
9
27
1,474
19
258
421
5
1
7
364
13
13
Nation of HEI
England
Northern Ireland
Scotland
Wales
53
Table 19 provides further detail on the reasons for leaving recorded by students who left with no
award or a lower award than they initially aimed to achieve. There are a number of interesting
differences between the disciplines in respect of students’ reasons for leaving under these
categories. Students who had failed to progress academically were the largest sub-category of
leavers, comprising 29% of those leaving without their award. Some disciplines recorded notably
higher proportions of students leaving without their award because of academic failure. These
include Computer Science (38%), Economics (40%), Finance and Accounting (38%), Marketing
(45%) and Medicine and Dentistry (64%). Disciplines recording notably lower percentages of
students leaving without their award because of academic failure included Education (20%), Music,
Dance and Drama (21%), Philosophy and Religious Studies (18%) and Social Work and Policy
(20%). Looking more broadly, the majority of STEM disciplines, as well as the majority of Social
Science disciplines, recorded higher percentages of students leaving for this reason while the
majority of Arts and Humanities disciplines record lower than average percentages. Health
disciplines were divided between those with higher percentages (Medicine and Dentistry and
Veterinary Medicine) and those with below average or average percentages (Health, Nursing, and
Social Work and Policy).
Some groups of students were over-represented within the group of those leaving as a result of
academic failure. These included men, students from socio-economic classes three to nine,
traditional age students and BME students. The strongest case of over-representation occurred in
relation to BME students where all groups of students with ethnic minority backgrounds, except
Chinese students, were over-represented in the category of students who leave their course
through academic failure. Black students accounted for 11% of students in this category overall,
despite such students representing 5% of students overall. ‘Asian’ students accounted for 12% of
students in this category despite this group of students comprising 8% of students overall. It is
notable that the list of disciplines that had comparatively low percentages of students leaving
because of academic failure overlapped considerably with the list of disciplines where BME
students were under-represented. Conversely, most of the disciplines with higher percentages of
academic failure overlapped with disciplines where BME students were over-represented. It is
unsurprising, therefore, that BME students were over-represented in the category of students
leaving due to academic failure. Furthermore, many of the disciplines with the highest percentages
of students leaving through academic failure recorded that over 30% of those leaving for this
reason were BME students: Biological Sciences, Business and Management, Computer Science,
Economics, Finance and Accounting, Law, Marketing, Maths and Statistics, Medicine and Dentistry,
and Politics. BME students’ concentration in these disciplines forms part of the picture of why BME
students experienced higher rates of non-continuation overall.
‘Other personal’ reasons for leaving accounted for the second largest group of students
withdrawing. Against a sector rate of 22%, some disciplines had notably higher percentages of
students in this category, namely History (32%), Languages (34%), Music, Dance and Drama (32%)
and Philosophy and Religious Studies (32%). It is perhaps noteworthy – as can be seen in table 11
above – that both History and Philosophy and Religious Studies had higher percentages of students
who reported ‘two or more impairments’.
Against a sector rate of 2% of non-continuation students leaving for ‘Health’ reasons, History (5%)
and Philosophy and Religious Studies (7%) stood out at the upper end as disciplines with more
students leaving under this category, while Other records 0% of students under this heading.
It is notable that all disciplines recorded that less than 3% of their non-continuation students had
left because of financial reasons.
54
Against a sector rate of 4% of students leaving due to ‘Exclusion’, some disciplines showed rates
twice as high or more; these were GEES (9%), History (10%), Other (9%), Politics (8%), Social
Work and Policy (9%), Psychology (10%) and Sociology (8%). One discipline – Veterinary Medicine
– recorded no students leaving because of exclusion24. Overall, mature students, men, students
from socio-economic classes three to nine and students without a parent with HE qualifications,
and BME students were over-represented in the category of students excluded from their
courses. ‘Black or Black British – African’ students were the most heavily over-represented in this
category, representing 12% of excluded students despite only representing 4% of all students.
Chinese students were the only ethnic minority group not over-represented in this category of
leavers.
24
Differences in reporting practices may underlie some of the variation across disciplines in relation to exclusion.
55
Table 19: Students25 who left with no award or a lower award than intended by reason for leaving
Discipline
Discipline
Completing a
course
%
No.
Failing
academically
%
No.
%
No.
2
Finance
%
No.
2
Other
personal
%
No.
22
Written off
after time
%
No.
5
Exclusion
%
No.
4
Left for
employment
%
No.
2
Other
%
No.
Sector as a whole
20
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport and
Tourism
Languages
Law
Marketing
Maths and Statistics
Media and Communications
Medicine and Dentistry
Music, Dance and Drama
Nursing
Other
Philosophical and Religious
16
20
18
14
20
15
21
22
17
20
14
27
9
712
417
411
737
1,025
59
975
1,158
230
198
101
857
105
22
30
35
33
38
40
20
36
29
38
28
23
24
1,009
638
791
1,751
1,898
161
955
1,894
394
395
197
725
287
4
2
1
2
1
2
4
1
3
2
3
3
5
165
47
29
89
67
6
164
60
39
19
24
100
56
3
3
2
2
2
2
2
2
2
3
3
3
3
142
52
52
121
97
7
115
113
20
26
18
94
31
28
23
19
19
18
26
29
16
22
16
27
24
32
1,261
477
417
1,035
898
104
1,362
816
300
161
194
737
377
6
4
4
5
5
4
6
4
7
6
6
4
6
273
74
100
286
244
15
270
199
94
63
41
123
66
2
4
2
6
4
5
3
3
7
4
9
2
10
95
73
46
319
193
22
150
155
97
42
60
67
117
3
2
2
2
2
2
2
3
1
3
2
1
1
116
44
55
114
86
7
110
132
14
30
11
45
14
17
14
16
16
11
6
13
13
12
10
9
12
10
772
288
358
874
559
25
593
674
165
98
62
385
122
15
587
33
1,265
2
66
2
93
26
1,019
6
225
2
82
4
161
10
398
3
18
11
28
15
2
18
17
48
12
48
407
60
215
230
4
323
952
2,674
69
34
36
45
34
26
64
21
29
20
18
650
802
249
257
394
131
380
1,624
1,105
106
1
3
2
2
3
3
4
4
0
7
13
56
9
16
43
6
79
235
17
39
1
3
2
1
2
1
3
2
0
2
17
74
10
9
29
2
60
85
13
10
34
21
17
19
25
21
32
26
3
32
636
472
96
145
379
43
585
1,432
173
191
2
5
7
1
7
6
4
2
4
35
102
41
10
111
102
223
87
23
2
5
2
5
3
2
2
2
9
2
43
109
13
38
51
5
28
126
492
12
1
1
3
2
2
2
1
0
1
15
23
16
13
27
34
48
1
7
23
9
11
8
16
7
13
14
19
22
435
207
63
62
244
15
237
797
1,073
132
25
29
Health
14
27% of students who had left without their intended award, and where their reason for leaving was unknown, were removed for the purposes of this analysis.
56
Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
27
13
16
21
15
17
455
51
307
577
243
56
27
34
24
20
28
31
458
136
454
531
471
101
2
3
3
4
3
4
34
10
65
94
57
13
1
2
2
2
2
2
23
8
41
46
37
7
28
26
26
30
31
24
462
106
492
774
1,506
78
2
3
6
5
4
3
39
11
111
146
73
9
2
8
10
9
8
-
35
33
181
231
124
-
1
2
2
2
2
4
23
9
46
49
35
13
9
10
11
10
7
16
149
41
207
271
114
52
57
Attainment26
Across the sector as a whole, 65% of students achieved a ‘upper degree’ (Table 20). There were
wide variations across disciplines in terms of the achievement of upper degrees so that 80% of
students within History, 78% within Languages, 76% within English and 88% within Medicine and
Dentistry were awarded a first class degree or an upper second (2:1), while only 56% were
awarded either of these degree classifications within Business and Management and Computer
Science, along with 55% within Hospitality, Leisure, Sport and Tourism, and 58% within Nursing
and Social Work and Policy.
All but one discipline (Art and Design) within the broad Arts and Humanities area recorded higher
rates of upper degrees than the sector as a whole. Five out of eight STEM disciplines also
recorded higher rates of upper degrees. By contrast, seven out of nine Social Science disciplines
(Business and Management, Education, Finance and Accounting, Hospitality, Leisure, Sport and
Tourism, Law, Marketing and Sociology) had lower rates of upper degrees than the sector as a
whole. Disciplines within Health and Social Care were evenly split; Health and Medicine and
Dentistry had higher than sector average rates of upper degrees, while Veterinary Medicine
matched the sector average, and Nursing, Social Work and Policy had lower rates of upper
degrees.
26
The sample analysed in relation to the achievement of an ‘upper degree’ included all students who qualified for a
degree in the reporting period except those who were not classifiable. The remaining sample of students is n =
376,765. HESA notes: “The classification of a first degree indicates the qualification class obtained. Certain
qualifications obtained at first degree level are not subject to classification of award, notably medical and general
degrees. These, together with ordinary degrees and aegrotat qualifications have been included within ‘unclassified’.
Third class honours, fourth class honours and the pass have been aggregated as third class/pass. Lower second and
undivided second class honours have been aggregated as lower second class.” As degrees not eligible for classification
are indistinguishable within this dataset from those which were eligible for classification but failed to reach the
required threshold, all ‘unclassified’ degrees have been removed from the dataset for the purpose of this analysis. In
the case of some disciplines, large percentages of students have been removed: Education (59%); Languages (41%);
Medicine and Dentistry (85%); Nursing (72%); Other (69%); Social Work and Policy (48%); Veterinary Medicine (58%).
58
Table 20: Attainment of a ‘upper degree’ by discipline
Discipline
% of students
achieving a
‘upper degree’
Number
% of students not
achieving a ‘upper
degree’
Number
Sector as a whole
65
35
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport
and Tourism
Languages
Law
Marketing
Maths and Statistics
Media and Communications
Medicine and Dentistry
Music, Dance and Drama
Nursing
Other
Philosophical and Religious
Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
61
65
63
56
56
69
61
66
76
59
71
69
80
13,973
6,748
5,969
13,053
6,293
3,593
7,676
12,033
7,085
3,852
5,292
10,608
8,047
39
35
38
44
44
31
39
34
24
41
29
31
21
8,847
3,667
3,412
10,286
4,877
1,601
4,936
6,180
2,290
2,698
2,123
4,732
2,071
55
7,142
46
5,969
78
61
63
67
66
88
77
58
59
2,454
8,089
2,017
3,033
4,957
877
8,065
3,904
595
22
39
37
33
34
12
23
42
41
704
5,225
1,182
1,532
2,568
123
2,471
2,865
416
75
2,015
25
678
66
73
73
58
62
65
4,170
2,549
8,014
3,973
3,954
575
34
27
27
42
38
36
2,118
936
3,018
2,913
2,391
316
59
Tables 21a-c27 provide further detail on the composition of students who achieved an upper
degree as compared to those who did not. Looking at the sector overall, there were small, but
noteworthy, differences between the rate at which diverse groups of students achieved an upper
degree or not. There were also notable variations in upper degree rates between difference
groups of students across the range of disciplines.
Age impacted on students’ achievement of an upper degree. Overall, 66% of traditional age
students achieved a ‘upper degree’ as against 61% of mature students who did. In 22/30 disciplines,
traditional age students achieved a higher rate of upper degrees than mature students; in all
disciplines but Art and Design, Built Environment, Education, Media and Communications, Social
Work and Policy, Veterinary Medicine, GEES and Language. In some disciplines where traditional
students achieved higher percentages of ‘upper degrees’, the difference between the two age
groups was larger than it was in others. For instance, while in Biological Sciences 65% of traditional
age students achieved an upper degree as against 63% of mature students, in Economics, 70% of
traditional students achieved one as against 51% of mature students, and in Marketing, 65% of
traditional students achieved one against 48% of mature students who did so.
In terms of gender, overall, 67% of women achieved a ‘upper degree’ against 62% of men. Women
achieved higher percentages of upper degrees in 27/30 disciplines; only in Built Environment,
Philosophy and Religious Studies, and Social Work and Policy did men secure one more often and
their advantage over women in these disciplines was marginal in all cases – only a 1-2% lead.
Conversely, in some of the disciplines where women secured higher percentages of upper degrees
than men, their lead was more substantial; for example, it was13-14% higher in GEES, Hospitality,
Leisure, Sport and Tourism, Marketing, and Veterinary Medicine. As was the case with noncontinuation, this finding was of particular interest as men were not more likely than women to
possess intersecting characteristics that were also related to lower attainment, such as mature
status, lower SEC etc.
Socio-economic class impacted on students’ achievement of an upper degree. Overall, 71% of
students from socio-economic classes one and two achieved an upper degree, while 65% of
students from socio-economic classes three to nine achieved one, and 59% of students with
missing data on this measure achieved one. In 27/30 disciplines, students coming from socioeconomic classes one and two were more likely to secure an upper degree than students coming
from socio-economic classes three to nine or students with missing data on this measure. The
exceptions to this rule were Business and Management, Nursing, and Physical Science. While in
some disciplines the differences were relatively narrow, in others they were larger so that in
English, 83% of students from socio-economic classes one and two achieved an upper degree,
against 76% of those identified as from socio-economic classes three to nine, and 65% of those
with missing data. Similarly in Law, 70% of students from socio-economic classes one and two
achieved an upper degree, against 60% of those identified as from classes three to nine, and 54% of
those with missing data. In Other, 75% of students from socio-economic classes one and two
secured an upper degree, against 59% of those in classes three to nine and only 48% of those with
missing data.
Similarly, overall, 70% of students reporting a parent with HE qualifications achieved an upper
degree, as against 64% of students reporting no parent with HE qualifications and 60% of students
with missing data on this measure. In most disciplines, a higher percentage of students who
reported a parent with an HE qualification achieved an upper degree. The exceptions to this rule
27
Please note that information against the UCAS point measure is not included here due to the limited amount of
data available in relation to the degree qualifiers category.
60
included Computer Science, where students who were not first generation had a marginal lead on
upper degree attainment, and Medicine and Dentistry and Physical Science where students with a
parent with an HE qualification had attainment rates matched by students who were first
generation.
Generally speaking, White students (70%) had a greater likelihood of achieving an upper degree
than BME students (52%); 55% of students whose Ethnicity data was missing achieved an upper
degree. In all but eight disciplines, a higher percentage of White students achieved an upper degree
than BME students28. The exceptions were: GEES, History, Hospitality, Leisure, Sport and
Tourism, Law, Marketing, Medicine and Dentistry, Music, Dance and Drama, and Sociology. In all
of these disciplines, Asian students, particularly Chinese students, secured a higher percentage of
upper degrees than other BME students. BME students were more likely to be men and to be
identified as from socio-economic classes three to nine and so there are some intersecting
background differences that are linked to this group and also with lower attainment. It is further
notable, however, that in most of those disciplines that are rich in upper degrees, an underrepresentation of BME students is also observable (English, GEES, History, Languages, Music,
Dance and Drama, Philosophy and Religious Studies). Conversely, BME students are overrepresented in some key disciplines awarding lower percentages of upper degrees as compared to
the whole-sector rate; namely Business and Management, Computer Science, Finance and
Accounting, Law, Marketing, Social Work and Policy.
Disability status impacted on students’ achievement of an upper degree. Overall, 66% of students
reporting a disability attained an upper degree, whereas 63% of students with a specific learning
disability (by far the largest group of disabled students) attained an upper degree. In all but three
disciplines – Business and Management, Economics, and Finance and Accounting – students
reporting a disability were less likely to achieve an upper degree. The percentage difference
between the two groups was largest in Languages, Medicine and Dentistry, Music, Dance and
Drama, Psychology, and Veterinary Medicine, but remained under 10% across all disciplines.
Mode of study also impacted on students’ achievement of an upper degree. Overall, 66% of fulltime students achieved an upper degree as against 52% of part-time students. With the exception
of Built Environment, in all29 HE disciplines full-time students secured higher percentages of upper
degrees than did part-time students. Again, while the advantage that part-time students enjoyed in
terms of upper degrees was comparatively small in the three disciplines where they secured
greater percentages of them, in some disciplines where full-time students had the secured
proportionately more, their lead was more considerable. For example, in Economics, Finance and
accounting, Marketing, Music, Dance and Drama, and Politics, the lead full-time students had over
part-time students was 30% or higher.
Overall, similar percentages of EU (64%) and UK (67%) students achieved an upper degree and,
while EU students secured higher percentages of them in around half of the disciplines, UK
students achieved higher percentages in the other half. Only 49% of non-EU students achieved an
upper degree overall, however, and the gap between this group of students and EU and UK
students in terms of this achievement measure was considerable in some disciplines. For example,
in English, while 66% and 78% of EU and UK students respectively secured an upper degree, only
34% of non-EU students do so. Non-EU students nonetheless secured the highest percentage of
upper degrees in Veterinary Medicine (85%, although note the small number of students here).
28
Please note: this finding excludes cases where < 5 students from a BME background are in a cell (Tables 21a-c).
29
No part-time students were recorded for Medicine and Dentistry and so ‘all’ here refers to the remaining 26 HEA
disciplines.
61
The distance between a student’s pre-HE address and their university also impacted on their
attainment. Across the sector as a whole students who travelled further afield to their HEI (70%)
were considerably more likely to attain an upper degree than students who travelled less than 30
miles (61%); students with missing data on this measure were the least likely to attain an upper
degree (56%). In 29/30 disciplines, students identified as travelling over 30 miles to their HEI
achieved a higher percentage of upper degrees over students attending a closer institution; the
exception being in Medicine and Dentistry where 90% of students travelling 30 miles or less
achieved an upper degree as against 87% travelling further. It should be remembered that for this
discipline 85% of students have been removed for the purposes of this analysis as their degrees
were not subject to the same classification procedures as the rest of the sector. In 28/30
disciplines (all but Medicine and Dentistry and Physical Science), students studying at an institution
further than 30 miles from their pre-HE address also achieved a higher percentage of upper
degrees than students with missing data on this measure.
Mode of study also impacted on students’ achievement of an upper degree. Overall, 66% of fulltime students achieved an upper degree as against 52% of part-time students. With the exception
of Built Environment, in all30 HE disciplines full-time students secured higher percentages of upper
degrees than did part-time students. Again, while the advantage that part-time students enjoyed in
terms of upper degrees was comparatively small in the three disciplines where they secured
greater percentages of them, in some disciplines where full-time students had the secured
proportionately more, their lead was more considerable. For example, in Economics, Finance and
accounting, Marketing, Music, Dance and Drama, and Politics, the lead full-time students had over
part-time students was 30% or higher.
Overall, similar percentages of EU (64%) and UK (67%) students achieved an upper degree and,
while EU students secured higher percentages of them in around half of the disciplines, UK
students achieved higher percentages in the other half. Only 49% of non-EU students achieved an
upper degree overall, however, and the gap between this group of students and EU and UK
students in terms of this achievement measure was considerable in some disciplines. For example,
in English, while 66% and 78% of EU and UK students respectively secured an upper degree, only
34% of non-EU students do so. Non-EU students nonetheless secured the highest percentage of
upper degrees in Veterinary Medicine (85%, although note the small number of students here).
The distance between a student’s pre-HE address and their university also impacted on their
attainment. Across the sector as a whole students who travelled further afield to their HEI (70%)
were considerably more likely to attain an upper degree than students who travelled less than 30
miles (61%); students with missing data on this measure were the least likely to attain an upper
degree (56%). In 29/30 disciplines, students identified as travelling over 30 miles to their HEI
achieved a higher percentage of upper degrees over students attending a closer institution; the
exception being in Medicine and Dentistry where 90% of students travelling 30 miles or less
achieved an upper degree as against 87% travelling further. It should be remembered that for this
discipline 85% of students have been removed for the purposes of this analysis as their degrees
were not subject to the same classification procedures as the rest of the sector. In 28/30
disciplines (all but Medicine and Dentistry and Physical Science), students studying at an institution
further than 30 miles from their pre-HE address also achieved a higher percentage of upper
degrees than students with missing data on this measure.
30
No part-time students were recorded for Medicine and Dentistry and so ‘all’ here refers to the remaining 26 HEA
disciplines.
62
Table 21a: Art and Design – Finance and Accounting – Attainment of a ‘upper degree’ by discipline, further detail31
Art and
Design
% 1st and 2:1
Biological
Science
Built
Environment
Business and
Management
Computer
Science
Economics
Education
Engineering
English
Finance and
Accounting
Age
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
Traditional
Mature
60
66
10,971
3,056
65
63
5,895
853
61
66
4,048
1,648
58
49
10,394
2,658
58
52
4,852
1,441
70
51
3,471
122
60
63
4,825
2,851
67
62
9,666
2,467
77
69
6,098
987
60
54
3,215
637
59
62
4,859
9,114
60
68
2,546
4,202
63
62
4,109
1,587
51
61
6,044
7,009
56
57
5,221
1,072
68
71
2,367
1,226
56
62
804
6,872
65
71
9,977
2,056
74
76
1,914
5,171
57
61
1,989
1,863
Gender
Men
Women
Socio-economic class (SEC)
One and two
Other SEC
Unknown
66
60
58
4,771
4,550
4,652
70
64
60
2,776
2,061
1,911
66
61
61
1,864
1,317
2,515
61
63
48
3,834
3,070
6,149
64
57
51
1,839
1,926
2,528
76
70
63
1,425
851
1,317
64
60
59
2,146
2,942
2,588
73
66
63
3,676
2,706
5,651
83
76
65
3,046
2,237
1,802
66
65
53
952
1,072
1,828
64
61
59
4,880
3,896
5,197
70
63
59
2,909
1,834
2,005
66
65
60
1,745
1,359
2,592
61
60
49
4,415
3,660
4,978
58
60
53
1,831
1,966
2,496
72
71
64
1,604
829
1,160
64
60
59
1,997
3,277
2,402
67
64
67
3,376
2,248
6,409
83
73
67
3,121
2,164
1,800
62
62
54
1,254
1,159
1,439
31
85
48
29
44
38
46
139
42
58
64
16
39
73
51
53
53
34
50
25
31
72
41
143
41
87
42
372
36
185
56
100
32
40
45
261
51
30
53
206
43
21
35
9
40
8
44
31
37
20
60
6
35
7
41
13
75
9
48
11
49
187
56
201
45
124
54
551
47
255
68
321
41
77
59
297
64
79
59
221
44
53
42
121
46
65
44
237
40
165
58
77
39
99
51
148
58
46
61
164
30
23
51
44
46
17
42
104
44
71
75
45
42
52
36
34
68
32
58
62
45
125
55
52
49
40
56
136
48
74
73
80
44
7
67
134
75
18
53
64
48
89
51
87
52
32
53
140
37
106
68
63
47
20
51
141
74
23
45
68
Parent HE
Yes
No
Unknown
Ethnicity
Black or Black British
Caribbean
Black or Black British
African
Other Black
background
Asian or Asian
British -Indian
Asian or Asian
British -Pakistani
Asian or Asian
British -Bangladeshi
Chinese
Other Asian
background
31
Please note that there is no analysis of students’ achievement of upper degrees by UCAS points in these tables as there was insufficient data on the UCAS point measure.
63
Other ethnic
background
White
Unknown
55
484
58
215
57
128
57
352
56
198
70
118
56
146
61
293
77
228
63
95
64
57
11,158
1,676
69
61
5,082
765
67
54
4,442
715
70
43
7,186
3,805
65
48
4,048
1,113
77
60
1,799
968
63
55
7,020
135
73
60
7,019
3,640
79
52
6,100
486
72
49
1,686
1,250
No known disability
62
12,146
66
7,080
63
5,540
56
1,5418
59
6,898
69
5,126
61
7,420
67
12,730
76
9,943
60
5,519
Known disability
58
2,359
61
676
61
551
61
920
57
655
69
278
56
602
65
941
72
811
62
218
61
54
13,608
365
66
48
6,517
231
62
64
4,410
1,286
57
49
11,963
1,090
59
37
5,876
417
70
28
3,568
25
63
53
6,592
1,084
66
63
10,998
1,035
77
63
6,660
425
60
30
3,746
106
50
65
62
744
773
12,456
55
67
65
330
347
6,071
53
52
64
335
292
5,069
34
60
64
2,063
1,595
9,395
42
61
58
592
426
5,275
56
73
73
647
286
2,660
50
60
61
37
57
7,582
60
61
69
2,662
826
8,545
34
66
78
172
191
6,722
46
65
65
1,003
218
2,631
1,878
2,874
944
58
70
44
3,651
5,273
4,129
56
63
48
2,586
2,451
1,256
67
75
60
549
2,075
969
59
63
56
3,735
3,431
510
63
72
61
2,622
5,533
3,878
73
82
56
1,737
4,571
777
62
69
50
1,293
1,252
1,307
11,230
327
810
686
56
69
61
51
5,298
239
449
307
69
65
79
64
3,299
32
162
100
61
80
63
51
6,446
262
454
514
66
70
67
67
75
69
86
74
6,110
98
412
465
57
74
62
63
Disability
Mode of study
Full-time
Part-time
Country of domicile
Non-EU
EU
UK
Distance between pre-HEI domicile and HEI
30 miles or less
Above 30 miles
Distance unknown
60
63
57
4,099
7,855
2,019
57
69
61
1,566
4,251
931
63
66
55
61
59
65
59
12,225
139
789
820
64
77
70
64
5,184
137
847
580
64
55
58
56
Nation of HEI
England
Northern Ireland
Scotland
Wales
4,724
199
553
220
55
64
66
52
9,839
327
1118
749
3,000
192
421
239
64
Table 21b: GEES - Medicine and Dentistry - Attainment of a ‘upper degree’ by discipline, further detail
st
% 1 and 2:1
GEES
Health
History
Hospitality,
Leisure,
Sport and
Tourism
Language
Law
Marketing
Maths and
Stats
Media and
Communications
Medicine and
Dentistry
Age
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
Traditional
Mature
71
71
4,900
392
70
66
7,811
2,797
80
74
7,024
1,023
55
54
6,006
1,136
78
78
2,151
303
62
54
7,004
1,085
65
48
1,807
210
67
64
2,866
167
66
67
4,281
676
88
86
783
94
65
78
2,518
2,774
66
70
2,862
7,746
77
82
3,676
4,371
48
61
3,243
3,899
75
79
745
1,709
59
62
2,880
5,209
55
69
719
1,298
65
69
1,719
1,314
64
68
2,112
2,845
85
90
370
507
Gender
Men
Women
Socio-economic class (SEC)
One and two
Other SEC
Unknown
75
70
67
2,647
1,591
1,054
73
69
67
3,685
3,362
3,561
84
78
75
3,906
2,210
1,931
59
54
50
2,597
2,538
2,007
80
76
75
1,184
610
660
70
60
54
3,013
2,347
2,729
71
68
52
757
633
627
70
66
62
1,337
926
770
68
67
63
1,706
1,741
1,510
91
89
83
469
126
282
75
69
67
2,649
1,400
1,243
73
69
65
3,851
3,296
3,461
84
77
76
3,775
2,133
2,139
58
55
51
2,439
2,564
2,139
79
78
76
972
566
916
68
61
54
3,150
2,517
2,422
66
64
60
699
609
709
69
67
63
1,241
908
884
69
66
63
1,714
1,648
1,595
87
87
88
437
93
347
44
4
47
59
62
21
33
54
44
8
40
83
44
28
55
11
42
53
50
1
28
7
45
317
61
30
29
58
41
9
44
281
43
46
47
41
50
78
67
12
-
-
35
13
50
2
24
6
38
3
31
10
46
6
20
1
47
14
50
1
56
33
66
860
71
92
40
66
76
19
53
381
50
59
60
163
46
65
88
83
20
3
55
378
62
33
25
15
46
5
44
331
49
22
57
51
57
28
86
24
78
7
58
92
46
13
37
7
75
6
46
111
88
7
65
37
41
12
86
6
64
62
18
13
67
58
127
206
85
70
17
26
58
33
38
13
63
50
10
11
69
44
70
71
41
50
9
11
60
58
56
58
56
55
23
17
88
89
21
32
Parent HE
Yes
No
Unknown
Ethnicity
Black or Black
British Caribbean
Black or Black
British African
Other Black
background
Asian or Asian
British -Indian
Asian or Asian
British -Pakistani
Asian or Asian
British -Bangladeshi
Chinese
Other Asian
65
background
Other ethnic
background
White
Unknown
66
93
63
322
77
211
48
197
71
94
58
308
58
68
61
89
61
169
89
49
73
62
4,820
294
74
68
6,963
1,271
80
80
7,138
464
57
50
5,944
744
79
80
1,996
293
69
54
5,041
1,402
73
47
1,389
372
70
60
2,141
385
69
62
3,826
672
88
90
535
113
No known disability
71
5,457
70
10,906
80
8,448
55
7,472
79
5,269
61
8,915
64
2,377
67
4,717
67
6,703
82
1,188
Known disability
69
659
63
1,059
73
905
53
623
71
342
59
599
63
177
65
236
60
591
74
62
72
53
5,196
96
71
49
10,024
584
81
68
7,468
579
55
35
6,955
187
78
70
2,363
91
63
36
7,775
314
64
30
1,991
26
67
40
2,980
53
66
57
4,763
194
88
-
877
-
53
69
72
125
100
5,067
64
72
69
608
514
9,486
74
84
80
132
188
7,727
42
58
55
258
415
6,469
75
78
78
50
171
2,233
53
58
62
910
400
6,779
41
54
68
175
173
1,669
50
71
68
188
135
2,710
56
71
66
326
291
4,340
87
100
88
64
19
794
Disability
Mode of study
Full-time
Part-time
Country of domicile
Non-EU
EU
UK
Distance between pre-HEI domicile and HEI
30 miles or less
Above 30 miles
Distance unknown
65
74
62
769
4,141
382
65
72
69
3,372
5,518
1,718
73
82
73
1,408
5,798
841
50
58
50
1,950
4,290
902
74
79
76
413
1,731
310
56
67
55
2,529
4,004
1,556
64
71
48
566
1,050
401
67
69
58
717
1,932
384
63
68
64
1,358
2,808
791
90
87
92
170
588
119
72
63
76
60
4,438
102
403
349
68
80
76
76
8,530
476
1,043
559
81
82
82
62
6,998
92
595
362
54
58
58
57
6,075
94
410
563
79
57
78
68
2,110
31
168
145
60
74
77
50
6,899
197
587
406
62
76
79
52
1,714
65
154
84
66
59
75
66
2,646
23
235
129
66
58
73
60
4,490
41
226
200
90
100
83
79
641
1
179
56
Nation of HEI
England
Northern Ireland
Scotland
Wales
66
Table 21c: Music, Dance and Drama – Veterinary Medicine - Attainment of a ‘upper degree’ by discipline, further detail
% 1st and 2:1
Music,
Dance and
Drama
Nursing
Other
Philosophy
and Religious
Studies
Physical
Science
Politics
Psychology
Social Work
and Social
Policy
Sociology
Veterinary
Medicine
Age
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
%
No.
Traditional
Mature
77
71
7,114
951
60
57
1,170
2,734
64
49
429
166
77
67
1,704
311
67
64
3,851
319
74
62
2,345
204
74
67
6,880
1,134
53
61
1,428
2,545
63
61
3,217
737
63
70
458
117
74
79
3,158
4,907
51
58
291
3,613
50
64
174
421
76
74
974
1,041
66
68
2,498
1,672
71
76
1,438
1,111
68
74
1,345
6,669
59
57
593
3,380
60
63
928
3,026
53
67
78
497
Gender
Men
Women
Socio-economic class (SEC)
One and two
Other SEC
Unknown
81
76
73
3,021
2,383
2,661
60
63
55
703
1,015
2,186
75
59
48
230
149
216
80
73
68
983
503
529
63
69
65
1,052
1,885
1,233
77
71
70
1,096
602
851
78
72
67
3,100
2,735
2,179
62
58
56
890
1,286
1,797
69
60
59
1,415
1,340
1,199
66
64
64
188
210
177
81
74
73
3,630
2,040
2,395
63
61
53
909
1,380
1,615
74
65
44
239
171
185
81
70
71
977
457
581
67
67
65
1,433
1,094
1,643
77
73
69
1,127
576
846
77
72
68
3,137
2,806
2,071
62
58
54
979
1,768
1,226
67
62
57
1,463
1,444
1,047
71
67
56
202
203
170
48
86
51
44
32
7
55
6
31
9
75
15
51
82
43
86
45
62
-
-
49
56
44
184
11
5
42
14
46
38
32
37
47
123
37
156
35
82
-
-
54
14
19
6
-
-
67
2
29
2
22
2
48
15
28
11
44
12
100
1
76
54
46
38
41
9
64
16
58
104
70
44
67
242
38
51
52
94
33
1
73
8
46
19
40
6
60
24
46
42
62
24
54
114
44
64
37
64
-
5
67
2
50
12
7
1
50
3
53
18
59
17
63
60
39
22
31
39
100
7
79
23
50
6
25
1
69
11
61
53
25
2
70
60
50
6
73
19
50
2
77
26
49
28
50
2
73
16
53
32
53
20
68
70
55
16
51
24
-
-
Parent HE
Yes
No
Unknown
Ethnicity
Black or Black British
Caribbean
Black or Black British
African
Other Black
background
Asian or Asian British
-Indian
Asian or Asian British
-Pakistani
Asian or Asian British
-Bangladeshi
Chinese
Other Asian
background
67
Other ethnic
background
White
Unknown
70
307
58
57
56
19
71
68
62
126
74
98
64
265
56
119
60
154
57
13
78
75
6,866
623
62
34
3,341
169
67
42
510
35
77
70
1714
141
68
66
3,285
461
77
72
1,814
476
76
68
6,383
600
61
61
3,330
112
66
64
3,149
255
65
66
521
37
No known disability
77
7,649
58
3,705
59
535
76
2,181
66
4,760
75
4,978
72
8,798
59
3,873
64
5,308
66
517
Known disability
69
1,182
56
289
57
60
73
306
62
448
71
509
66
857
51
573
61
583
57
71
77
47
7,992
73
61
51
2,732
1,172
66
41
469
126
75
65
1,917
98
67
54
4,087
83
74
41
2,503
46
74
56
7,660
354
59
52
3,345
628
63
53
3,658
296
65
59
559
16
74
74
77
234
311
7,520
22
62
60
76
55
3,773
35
59
60
13
17
565
75
73
75
45
52
1,918
56
77
67
183
184
3,803
61
80
73
159
268
2,122
65
71
73
216
302
7,496
61
74
58
34
28
3,911
54
75
62
75
115
3,764
85
41
64
28
9
538
Disability
Mode of study
Full-time
Part-time
Country of domicile
Non-EU
EU
UK
Distance between pre-HEI domicile and HEI
30 miles or less
Above 30 miles
Distance unknown
70
80
71
1,652
5,377
1,036
58
63
43
2,196
1,378
330
44
72
52
133
326
136
70
77
73
357
1,441
217
61
68
68
892
2,763
515
66
76
71
419
1,624
506
67
77
67
2,460
4,769
785
58
59
54
2,078
1,425
470
55
67
63
1280
2,196
478
60
67
63
88
321
166
77
68
75
76
7,198
71
300
496
58
60
67
51
3,309
273
119
203
60
42
580
15
74
75
85
69
1,610
51
219
135
67
69
62
61
3,515
49
374
232
73
71
79
74
2,057
51
248
193
72
76
78
71
6,629
205
631
549
58
72
51
52
3,331
246
158
238
62
67
60
62
3,462
105
277
110
63
96
48
518
47
10
Nation of HEI
England
Northern Ireland
Scotland
Wales
68
Conclusion
This report’s findings point to a complex mix of factors that lead to different continuation and
attainment rates across disciplines. It provides an overview of disciplinary differences for those
working and studying within HE, and suggests such differences constitute an important part of the
HE landscape that we should seek to understand better if we are committed to the reality of
widening access and achieving student success across a “diverse student body”, as well as to the
principle of supporting “a vibrant and cohesive intellectual, social and cultural environment” in our
universities (BIS 2014, p. 4).
The report provides information to enhance institutional awareness of disciplinary differences, to
better support, for instance, understanding of the extent to which local patterns of retention and
attainment reflect the national discipline profile.
The report also highlights the importance of reading the continuation and attainment rates of
different disciplines together in order to gain a fuller understanding of the specific HE contexts
within which students are attempting to succeed when they embark on their studies. It is notable,
for instance, that across the broad Arts and Humanities subjects, students find more favourable
retention and attainment rates. Also underscored is the importance of reading both the
continuation and attainment rates of different groups of students together to understand their
overall position. As unsettling as the lower attainment rates of BME students, part-time students,
and mature students are, their import can only be fully appreciated if we read them in the context
of the higher percentages of students from these groups who have already withdrawn from their
degree courses as compared to their White, full-time and traditional age counterparts. For
example, to fully comprehend the comparative position of BME and White students, the
attainment lag that BME students experience by contrast with White students needs to be read
alongside the fact that a higher proportion of BME students have already left their courses without
their degree.
Finally, the report supports the identification of areas that warrant further attention and
investigation. Improving understanding of why particular background characteristics create
disadvantage across all disciplinary contexts is important, as is the development of a more detailed
understanding of how students who are disadvantaged in one discipline are doubly so in another.
Developing more focused and richer understanding of how some groups of students experience
different disciplines, and how their background characteristics interact with a variety of disciplinary
contexts to become more or less vulnerable to withdrawal and low attainment is, therefore, an
important route for future research. Finally, in relation to several student characteristic measures
– socio-economic class, parental education, UCAS points and distance between pre-HE address
and HEI – there is a large amount of missing data in the HESA data set underpinning this report, as
there is in HESA statistics overall. Further research with more complete information against these
measures would enhance understanding of how these factors in particular impact on students’
performance within HE.
69
References
BIS (2014) National strategy for access and student success in higher education [Internet]. Department
of Business, Innovation and Skills. Available online from:
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/299689/bis-14-516national-strategy-for-access-and-student-success.pdf [Accessed 3 June 2014].
Boliver, V. (2014) Hard Evidence: why aren’t there more black British students at
elite universities? [Internet] The Conversation. Available online from:
https://theconversation.com/hard-evidence-why-arent-there-more-black-british-students-at-eliteuniversities-25413 [Accessed 3 June 2014]
Equality Challenge Unit/Higher Education Academy (2008) Ethnicity, gender and Degree
Attainment Project: Final Report. Available online from:
https://www.heacademy.ac.uk/resources/detail/resources/detail/inclusion/ethnicity_gender_and_de
gree_attainment_project [Accessed 1 December 2014]
Higher Education Academy (2011) Men in higher education: HEA Discussion paper. Available
online from: https://www.heacademy.ac.uk/resources/detail/retention/Male_Access_report
[Accessed 16 September 2014]
HEFCE (2014) Differences in degree outcomes: Key findings March 2014, Issues Paper: ref:
2014/03 [Internet]. Higher Education Funding Council for England. Available from:
http://www.hefce.ac.uk/pubs/year/2014/201403/ [Accessed 3 June 2014].
HEFCE (2013) Trends in young participation in higher education, Issues Paper: October 2013/28
[Internet]. Higher Education Funding Council for England Available from:
https://www.hefce.ac.uk/pubs/year/2010/201003/ [Accessed 3 June 2014]
70
Appendices
Appendix 1 - List of HEA disciplines
List of HEA disciplines with sub-disciplinary subject areas, and JACS codes
Art and Design
(W0) Broadly-based programmes within
creative arts and design
(W1) Fine art
(W2) Design studies
(W6) Cinematics and photography
(W7) Crafts
(W9) Others in creative arts and design
Biological Sciences
(C0) Broadly-based programmes within
biological sciences
(C1) Biology
(C2) Botany
(C3) Zoology
(C4) Genetics
(C5) Microbiology
(C7) Molecular biology, biophysics and
biochemistry
(C9) Others in biological sciences
(D4) Agriculture
(D5) Forestry
(D6) Food and beverage studies
(D7) Agricultural sciences
Built Environment
(K0) Broadly-based programmes within
architecture, building and planning
(K1) Architecture
(K2) Building
(K3) Landscape design
(K4) Planning (urban, rural and regional)
(K9) Others in architecture, building and
planning
Business and Management
(N0) Broadly-based programmes within
business and administrative studies
(N1) Business studies
(N2) Management studies
(N6) Human resource management
(N7) Office skills
(N9) Others in business and administrative
studies
Computer Science
(G02) Broadly-based programmes in
computer science
(G4) Computer science
(G5) Information systems
(G6) Software engineering
(G7) Artificial intelligence
(G92) Others in computing science
Economics
(L1) Economics
Education
(X0) Broadly-based programmes within
education
(X1) Training teachers
(X2) Research and study skills in education
(X3) Academic studies in education
(X9) Others in education
Engineering
(F2) Materials science
(H0) Broadly-based programmes within
engineering and technology
(H1) General engineering
(H2) Civil engineering
(H3) Mechanical engineering
(H4) Aerospace engineering
(H5) Naval architecture
(H6) Electronic and electrical engineering
(H7) Production and manufacturing
engineering
(H8) Chemical, process and energy
engineering
(H9) Others in engineering
(J1) Minerals technology
(J2) Metallurgy
(J3) Ceramics and glasses
(J4) Polymers and textiles
(J5) Materials technology not otherwise
specified
(J6) Maritime technology
(J7) Biotechnology
71
(J9) Others in technology
English
(Q2) Comparative literary studies
(Q3) English studies
(W8) Imaginative writing
Finance and Accounting
(N3) Finance
(N4) Accounting
Geography, Earth and Environmental
Sciences (GEES)
(F6) Geology
(F7) Science of aquatic and terrestrial
environments
(F8) Physical geographical sciences
(L7) Human and social geography
Health
(B0) Broadly-based programmes within
subjects allied to medicine
(B1) Anatomy, physiology and pathology
(B2) Pharmacology, toxicology and pharmacy
(B3) Complementary medicine
(B4) Nutrition
(B5) Ophthalmics
(B6) Aural and oral sciences
(B8) Medical technology
(B9) Others in subjects allied to medicine
History
(Q7) Classical Greek studies
(Q8) Classical studies
(Q9) Others in linguistics, classics and related
subjects
(V0) Broadly-based programmes within
historical and philosophical studies
(V1) History by period
(V2) History by area
(V3) History by topic
(V4) Archaeology
(V9) Others in historical and philosophical
studies
Hospitality, Leisure, Sport and Tourism
(C6) Sports science
(N8) Hospitality, leisure, tourism and
transport
Languages
(Q0) Broadly-based programmes within
languages
(Q1) Linguistics
(Q4) Ancient language studies
(Q5) Celtic studies
(Q6) Latin studies
(R1) French studies
(R2) German studies
(R3) Italian studies
(R4) Spanish studies
(R5) Portuguese studies
(R6) Scandinavian studies
(R7) Russian and East European studies
(R8) European studies
(R9) Others in European languages, literature
and related subjects
(T1) Chinese studies
(T2) Japanese studies
(T3) South Asian studies
(T4) Other Asian studies
(T5) African studies
(T6) Modern Middle Eastern studies
(T7) American studies
(T8) Australasian studies
(T9) Others in Eastern, Asiatic, African,
American and Australasian languages,
literature and related subjects
Law
(M0) Broadly-based programmes within law
(M1) Law by area
(M2) Law by topic
(M9) Others in law
Marketing
(N5) Marketing
Maths, Statistics and Operational
Research (OR)
(G01) Broadly-based programmes in
mathematical science
(G1) Mathematics
(G2) Operational research
(G3) Statistics
(G91) Others in mathematical sciences
Media and Communications
(P0) Broadly-based programmes within mass
communications and documentation
(P1) Information services
72
(P2) Publicity studies
(P3) Media studies
(P4) Publishing
(P5) Journalism
(P9) Others in mass communications and
documentation
Sociology
(L0) Broadly-based programmes within social
studies
(L3) Sociology
(L6) Anthropology
(L9) Others in social studies
Medicine and Dentistry
(A0) Broadly-based programmes within
medicine and dentistry
(A1) Pre-clinical medicine
(A2) Pre-clinical dentistry
(A3) Clinical medicine
(A4) Clinical dentistry
(A9) Others in medicine and dentistry
Veterinary Medicine
(D1) Pre-clinical veterinary medicine
(D2) Clinical veterinary medicine and
dentistry
(D3) Animal science
(D9) Others in veterinary sciences,
agriculture and related subjects
Music, Dance and Drama
(W3) Music
(W4) Drama
(W5) Dance
Nursing
(B7) Nursing
Other
(Y0) Combined
Philosophical and Religious studies
(V5) Philosophy
(V6) Theology and Religious studies
Physical Science
(F0) Broadly-based programmes within
physical sciences
(F1) Chemistry
(F3) Physics
(F4) Forensic and archaeological science
(F5) Astronomy
(F9) Others in physical sciences
Politics
(L2) Politics
Psychology
(C8) Psychology
Social Work and Policy
(L4) Social policy
(L5) Social work
73
Appendix 2 – Retention and attainment data set
Bespoke data set: 34843_RL – further information
Students in the data item one
This data set was provided in two packages: data items one and two. Data item one comprised
data on a series of student background and on-course variables; these included disciplinary area,
gender, socio-economic class, HEI attended, parental education, ethnicity, mode of study, broad
pre-HEI domicile, distance between pre-HEI address and HEI, pre-HEI qualifications tariff,
continuation status plus reason for leaving for non-continuing students, and class of degree.
Further derived variables were added, for example, on host nation of HEI.
Data item two included data on disability status, disciplinary area, class of degree, and continuation
status. Disability status was held in data item two separately from other variables to preserve
anonymity.
The analysis on data item one was undertaken on all undergraduate students registered as taking a
programme (within the time period) in a single discipline and so who were entirely aligned to, and
housed within, that discipline (n = 1,631,468 – this represents 85% of the total number of students
in the sample). Students taking joint/across discipline degrees (15%) were removed for the
purposes of analysis as HESA provides no record of the discipline that these students are mainly
aligned to and housed within. Students taking combined degrees under the discipline ‘Other’ were
included as these students are associated with the area of ‘Combined’ or ‘Other Studies’.
Students in data item two
The analysis on data item two (pertaining only to disability data) was undertaken on all
undergraduate students studying between 2010 and 2011 after students not within the Standard
Registration Population were removed (n = 1,915,644), and included students studying within each
discipline as part of their programme as well as those undertaking all of their studies within an
individual discipline. This was because students in data item two could not be further segregated.
74
Table 1: Students in data item two
Discipline
Art and Design
Biological Sciences
Built Environment
Business and Management
Computer Science
Economics
Education
Engineering
English
Finance and Accounting
GEES
Health
History
Hospitality, Leisure, Sport and
Tourism
Languages
Law
Marketing
Maths and Statistics
Media and Communications
Medicine and Dentistry
Music, Dance and Drama
Nursing
Other
Philosophical and Religious Studies
Physical Science
Politics
Psychology
Social Work and Policy
Sociology
Veterinary Medicine
Total
% of student body in the
discipline - data
No of students in
the discipline - data
Item two
Item two
5.1
3.4
2.4
7.6
4.1
1.6
5.5
6.1
3.3
2.3
1.9
4.8
2.9
98486
65941
46707
147097
79336
31149
106554
116880
64352
45035
37522
92568
56683
3.5
68564
2.8
3.7
0.8
2.0
2.3
2.4
2.4
8.1
5.4
0.8
2.2
1.6
3.8
2.9
2.3
0.5
100
54371
71334
16551
39882
44125
46370
47099
156036
103478
16755
43639
32433
74431
57201
44741
10324
1915644
75
Appendix 3 - HESA definitions non-continuation marker
Non-continuation (TQI)
Applies to all students within the HESA standard registration population, except postgraduate
research students and students on professional or non-credit bearing courses. Writing-up and
sabbatical students have also been excluded. It looks at progression from one year (y1) to the
next (y2). Linking is done using HIN (Husid-Institution-Numhus) which means that if a student
changes course or institution they will not be linked. For this reason, transfers and those no
longer in HE cannot be distinguished.
Continuing at institution – this is defined as all students who are progressing into their
following year of study.
Gained intended award or higher – for those students who are not progressing into their
following year of study, this is defined as those students who have achieved a qualification in either
of the two comparison years AND that qualification is deemed to be equivalent to or higher than
the qualification aimed for in the first of the two comparison years.
Gained other award - for those students who are not progressing into their following year of
study, this is defined as those students who have achieved a qualification in either of the two
comparison years AND that qualification is deemed to be lower than the qualification aimed for in
the first of the two comparison years.
Dormant – those students who have been recorded as dormant or writing-up status in the
second of the comparison years and who have not obtained a qualification.
Left with no award – those students who are not continuing into their following year of study,
have not been awarded a qualification in either of the two comparison years and are not recorded
as dormant status.
76
Appendix 4 - Background information on key demographic groups: nations
Table 1: Background information on key demographic groups: nations
Age
Gender
Mode of study
Socio-economic class
Parent HE
Ethnicity
UCAS points
Distance between
pre-HEI domicile and
HEI
% Young
% Mature
% Men
% Women
% Full-time
% Part-time
% One and two
% Other SEC
% Unknown
% Yes
% No
% Unknown
% BME
% White
% Unknown
% Above 340
% Below 340
% Unknown
% 30 miles or less
% Above 30 miles
% Distance
unknown
England
58
42
43
58
67
33
24
23
53
31
31
38
18
70
12
7
14
78
30
38
Northern
Ireland
66
34
40
60
73
27
22
32
46
18
14
68
1
84
15
8
13
80
23
54
Scotland
68
32
42
58
81
19
32
25
43
39
29
32
5
80
15
8
8
83
38
42
Wales
63
37
46
54
74
26
24
23
53
21
14
65
6
81
13
7
15
79
34
46
32
23
20
20
77
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