The academic experience of students in English universities
Bahram Bekhradnia, Carolyn Whitnall and Tom Sastry
1.
In March 2006, with a grant generously provided by the Higher
Education Academy, the Higher Education Policy Institute commissioned
Opinionpanel Research to undertake a survey of first and second year full time undergraduate students in English universities
1
. 23,000 students were asked about aspects of their university experience, including the amount of teaching received and private study undertaken. Around
15,000 replies were received. This report outlines some of the highlights of the analysis, which are reported fully on the HEPI website.
Workload
2.
The survey asked about both the amount of teaching received and private study undertaken. This has allowed a measure of total workload to be calculated by adding the two together. That is reported in paragraphs 8-11 after discussion of the amount of teaching that was scheduled and missed and the private study undertaken. The variation in workloads between subjects and, within subjects, between institutions, is perhaps one of the major findings of this survey.
Scheduled teaching
3.
Students reported an average (mean) of 13.7 hours of scheduled teaching per week. As figure 1 shows, subjects where the teaching load was highest 2 reported more than twice as much teaching as the lowest.
1 Opinionpanel Research kindly undertook the survey at cost price
2 Medicine and dentistry, veterinary and agriculture and subjects allied to medicine had the highest workload, languages and historical and philosophical studies the lowest

Figure 1: Scheduled hours of teaching per week by subject area 3
25.0
20.0
15.0
10.0
5.0
0.0
Ve te rin ary sci en ce s,
Me di
a gricu ci ne ltu
a re nd
d en
a nd
Su bj tist ry te d
re la ect s
En al su bj gi lie ne ect s erin di d to
me g an ci ne d te ch no lo gy
Ph ysi ca l sci en ce s
Ma th ema
, b ui ite ct ure
Arch en ce s d pl an ni tica l sci g an ld in
C omp ng ut er sci en ce
Ed
Bi ol uca og tio ica n l sci
C re at ive en ce s
a rts an d de si gn ist ra tive
Bu si ne ss an d
Ma ad ss min co mmu
st ud ie s ni ca tio ns an
La w d do cu me nt at io n
So ci al
st ud ie l a nd
p hi s ng ua ge s
La lo so ph ica l st ud ie
Al s l su bj ect s
H ist orica
4.
Given the large differences between subjects shown above, it would be misleading to compare raw data on the amount of teaching scheduled by each institution because we would not expect an institution specialising in the humanities to offer as much teaching as one specialising in medicine and health related studies. Therefore, a model has been created that allows for the different subject profiles of different institutions.
5.
Figure 2 (below) shows the differences between actual levels of scheduled teaching and levels predicted by the model. In 82 of 118 institutions the mean scheduled hours were within an hour of the level predicted by the model and 101 were within an hour and a half. Given that the mean workload across the system was over 13.7 hours that suggests that in general, where you study makes less difference than what you study.
3 The subject areas analysed in this report are standard HESA classifications. Nevertheless these group a number of disciplines within a subject that might have different characteristics, though that is unlikely materially to affect the conclusions. The figure for ‘all subjects’ is weighted to reflect the distribution of students between subjects in the HESA population. The same has been done for figures 3,5 and 10.

Figure 2: Difference between observed scheduled hours and the level predicted by the model in each institution
45
25
20
15
10
40
35
30
5
0
-3 -2 -1 0 1 2 3 4
Difference between actual levels (hours) and those predicted by the model
5
Hours missed
6.
The survey also asked students how many hours of timetabled teaching they missed. Students claimed to attend 92 per cent of timetabled sessions. Figure 3 shows that in no subject were more than
13 per cent of timetabled hours missed, though there are substantial differences between subjects.
Figure 3: Percentage of scheduled hours of teaching not attended - by subject area
14%
12%
10%
8%
6%
4%
2%
0%
C omp ce ut er sci en ist ra tive min
Bu si ne ss an d ad
st ud ie s al
st ud
So ci ie tica s
Ma th ema ss co mmu l sci en ce ni ca tio ns s an d do
La w cu me g nt at io n an d
En gi ne erin ite ct ure
, b
Arch te ch no ui ld in g
H lo ist gy an d pl an
Bi orica ol og ni ng ica l a nd
p en ce s l sci hi lo so ph ica
Ma ie s l st ud
Ph ysi ca l sci en
C re at ce s
La ng ua ive
a rts ge s an d de si
Me di ci gn ne
a nd
d nd
re la te ltu re
a en tist ry d su bj ect s d to
me
Su bj ect s al lie sci en ce s,
a gricu di ci ne
Ed uca tio n
Al l su bj ect s
Ve te rin ary

Private study
7.
It might be expected that those subjects with the least teaching contact might require the most private study, and indeed to some extent this appears to be so (see figure 4). For example Languages, Law and
History, where the least formal teaching is provided, require among the most private study. However, Mass Communications as well as Business and Administrative Studies provide some of the smallest amounts of scheduled teaching, and score least well in terms of private study too.
And the analysis of Total Workload (paragraphs 8-11 below) shows that private study is a long way from compensating for the smaller amounts of teaching provided in these subjects.
Figure 4: Hours of Private Study by subject
20.0
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
Arch ite ct ure
, b ui ld in g
H ist orica an d pl an ni ng
La w hi lo so ph ica
Me di ci l a nd
p l st ud ie s
d en tist ry ne
a nd s
La ng ua ge rts an d de si gn
re la te d su bj ect s
C re at ive
a ltu re
a nd tio n
Ed uca
So ci al
st ud ie s
me
C omp
Su bj ect s al lie d to
En gi di ci ne ut er sci en ce g an d ne erin sci en ce s,
a gricu te ch no lo gy
Bi ol og ica l sci en ce s en ce
Ph ysi ca l sci th ema tica s l sci ist
Bu si
Ma ne ss an d ss co mmu ad min ni ca tio ns en ce s
st ud ie s ra tive an d do cu me
Ma
Ve te rin ary nt at io n
Al l su bj ect s
Total workload
8.
The total student workload (attended hours of teaching plus private study) is a measure of how hard first and second year students work to obtain their degrees. Figure 5 shows that the average student claimed to spend a total of 25.7 hours either being taught or engaged in private study. There are notable differences between subjects: in medicine and dentistry students spend over 35 hours on academic work on average; in mass communications and documentation they spend less than 20 (19.9 hours). There is a general tendency for science and health-related subjects to have the highest workloads.

Figure 5: Student workloads: hours of teaching plus private study – by subject
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Me
Ve te rin ary,
Arch
d en tist ry di ci ne
a nd
a gr icu ltu ite ct ure re
a nd
re la te d g an d pl
, b ui ld in
Su bj ect s an al lie ni d ng to
me
En gi ne erin g di ci ne an d te ch no lo gy
Ph ysi ca l sci en ce s
La w
Ma
Ed uca th ema tio n tica l sci en ce s ut er sci en ce
C omp
C re at ive
a si gn rts an d de
Bi ol og ica l sci en ce s l a nd
p hi ua ge s
La ng lo so ph ica
H ist orica l st ud ie s
So ci ss an d
Bu si ne
Ma ss co mmu al
st ud ie ist ra s tive ad min ni ca tio ns an ie s
st ud d do cu me nt at io n
Al l su bj ect s
Private study Attended hours
9.
Table 6 provides separate figures for old and new universities. It is very noticeable that the differences between old and new universities in each subject are relatively small, whereas the differences between subjects are much larger.
Table 6: Total workload by subject and type of institution
Medicine and dentistry
Subjects allied to medicine
Biological sciences
Veterinary sciences, agriculture & related subjects
Physical sciences
Mathematical sciences
Computer science
Engineering and technology
Architecture, building and planning
Social studies
Law
Business and administrative studies
Mass communications and documentation
Languages
Historical and philosophical studies
Creative arts and design
Education
All subjects
Old universities
New universities
All universities
35.2
30.5
24.7
22.7
17.5
23.8
23.8
24.3
27.9
25.9
33.9
28.5
26.7
27.0
30.0
35.6
23.0
28.1
35.7
31.9
23.7
32.6
22.6
25.5
24.6
30.1
28.4
22.0
25.4
20.7
20.6
20.9
20.7
26.2
26.9
24.8
35.2
31.2
24.3
21.7
19.9
23.3
23.3
25.6
26.9
25.6
33.2
27.5
26.5
26.0
29.9
31.8
22.8
27.2

10.
There was considerable variation between institutions active in similar subjects4, as is shown in Table 7 below.
Table 7: Student workload by subject – highest and lowest institutional mean hours per week 5
Subject
Medicine & dentistry
Subjects allied to medicine
Biological sciences
Physical sciences
Mathematical sciences
Computer science
Engineering
Social studies
Law
Business & administrative studies
Mass communication & documentation
Languages
Historical & philosophical studies
Creative arts & design
Education
Highest institutional mean
45.1
42.5
43.7
44.7
35.2
34.4
41.6
33.4
39.4
26.6
23.9
36.7
32.2
37.6
35.8
Lowest institutional mean Median
29.0
22.1
19.1
36.5
32.4
25.4
18.9
19.9
16.9
24.7
17.8
19.2
17.1
27.1
25.2
23.2
31.8
22.0
26.6
21.0
15.9
16.0
17.4
16.7
22.6
21.1
22.9
22.8
24.9
28.8
11.
The full report contains a complete analysis of student workload by subject and institution, from which Table 7 is drawn. The extent of the differences is remarkable and raises important policy questions. In particular it raises questions about what it means to have a degree from an English university, if a degree can apparently be obtained with such very different levels of effort. The full report also provides information about the classification of degrees in different subjects at different universities, and about the UCAS tariff points of students on entry. It appears to show that some institutions award many more 2.1 and firstclass degrees than others, and there are subject differences too.
Explanations for this might be that the students concerned are more able, or else that they work harder. On the basis of these data, neither of these explanations appears to provide a complete answer. This report does not prove that the degree classification system is flawed, but it certainly raises questions that need to be addressed 6 .
4 The results have been adjusted to allow for year effects (different proportions of first and second year students) so these ought not to affect the outcome.
5 Two subjects - Veterinary sciences, agriculture and related subjects, and Architecture, building and planning
- are omitted from this analysis because there was an insufficient response in these subjects to achieve the required level of reliability.
6 It should be noted though that a model developed by HEFCE analysts indicates that the distribution of degree classes in different institutions is more or less what would be expected taking into account gender, entry qualifications and disciplines. See HEFCE 2003/32 Schooling effects on higher education achievement and HEFCE 2005/09 Schooling effects on higher education achievement: further analysis - entry at 19
(www.hefce.ac.uk). It may be that a refinement of the HEFCE model to include data on student workload would reveal that some degrees require less work than others: the raw data shown in the main report do not in themselves prove this but they suggest that the possibility is worthy of investigation. On the other hand, it should be noted also that a 1996 HEQC report “Inter-institutional variability of degree results: An analysis in selected subjects” appeared to show conclusively that differences in standard did exist between subjects and institutions

Does more mean better?
12.
This study does not assume that more taught hours lead to more learning – in fact there is ample academic literature that suggests that the optimal balance between teaching and private study is complex and depends on a number of factors not explored here, including teaching styles, course aims and so on.
13.
Moreover, the responses of students to the questions about this show that students too do not believe it is self-evident that more taught hours would be a good thing. The survey asked students to rate their satisfaction with the amount of teaching they received. As figure 8 shows, dissatisfaction is greatest amongst students with very low levels of teaching, followed by those with the most scheduled hours. The students least likely to be unhappy are those receiving 15 to 19 hours of scheduled teaching – slightly more than the current average figure of
13.7 hours.
Figure 8: Disagreement with proposition: ‘I am satisfied with the number of time-tabled classes I have had during this term’ by scheduled hours of teaching per week
45%
40%
35%
30%
25%
20%
15%
10%
5%
Disagree somewhat
Disagree strongly
0%
0 to 4 5 to 9 10 to 14 15 to 19 20 to 24 25 to 29 30 to 34
Scheduled hours
> 35
14.
Students were also asked to rank seven possible uses for additional revenue from higher fees. As table 9 shows, they gave much the highest priority to measures which would improve the quality of teaching
(smaller group sizes and better academic facilities); whereas the option of increasing the number of classes was much less popular.

Table 9: Ranking of suggested priorities for investing additional fee income
Top priority
31%
Average ranking
(lowest indicates highest priority)
3.1
Suggested priority
Reduce teaching group/ lecture sizes
Provide better library, laboratory or specialist academic facilities
Increase hours of time-tabled classes
Provide better social or sporting facilities
Better pay for staff
Better e-learning and web-based facilities
Improve security on campus
Total
26%
12%
10%
9%
8%
4%
100%
2.8
4.5
4.2
4.3
4.1
4.9
4
15.
the extent of small group teaching is therefore of particular interest.
Figure 10 shows that the average (mean) student receives 3.5 hours of teaching in groups containing up to 15 other students. There is considerable variability between subjects, with students in the biological sciences receiving less than two hours per week in small groups.
Figure 10: Amount of teaching in groups with 15 or fewer other students (in addition to the respondent) by subject area
6.0
5.0
4.0
3.0
2.0
1.0
0.0
C ive
a rts re at ite ct ure
, b an d de si gn an d ui ld in g
Me di pl an ci ne ni ca tio ns an
Arch
Ma ss co mmu ni ng
a nd
d en tist ry d do cu me
C nt at omp io n ut er sci en ce
La
Su bj ect s
En gi ne sci en ce s,
a gricu
Ve te rin ary ng ua ge s to
me al lie d di ci ne te ch no lo gy
re la te erin g an d ltu re
a nd d su bj ect s
Ph ysi ca l sci en ce s min
Bu si ne ss an d ad
La w ist ra tive
st ud ie s
Ed uca tio n tica
Ma th ema l sci en ce s
So ci al
st ud ie s l a nd
p hi lo so ph ica l st ud ie s
Bi ol og ica l sci en
H ist orica ce s
Al l su bj ect s
0-5 others 6-15 others
Old and new universities
16.
There were few large differences between old and new universities on most indicators but, perhaps contrary to received wisdom, where such differences exist they suggest that the new universities provide more

teaching than older ones 7 . The most interesting discrepancy reported in table 11 (below) relates to teaching in groups of 16 or less. New universities appear to have an advantage here as a result of the provision of extra hours in ‘seminar’ sized groups of 7-16 students.
Table 11: Comparison between old and new universities (figures weighted to reflect subject mix)
Mean scheduled hours of teaching per week
Mean total workload (hours per week)
Hours in groups of 16 or less
Hours in groups of 6 or less
Discussions with staff outside scheduled hours at least once per month (per cent)
Percentage of scheduled teaching not attended
Old
13.3
25.9
3.2
0.7
43
8
New
13.7
24.8
4.1
0.7
48
7
17.
Another indicator on which new universities differ from older ones is the use of non-academic staff to provide teaching. Table 12 shows that apart from lectures all forms of teaching are much more likely to be led by academics in new universities. This is not particularly surprising: old universities are generally more research intensive and have larger numbers of research students and postdoctoral researchers who need teaching experience as part of their preparation for future academic roles. What is interesting, however, is that there is no great discrepancy between old and new universities in the overall amount of teaching provided, suggesting that in old universities the use of non-academics substitutes for - rather than supplements - teaching by academics.
Table 12 Summary table - teaching led by academics by type of teaching (per cent)
Lectures
Seminars
Tutorials
Practicals
Fieldwork
Old universities
98
70
70
64
74
New universities
99
92
93
83
85
Impact of paid employment
18.
A recent survey for UUK and HEFCE found that term-time working has a measurable negative effect upon student attainment and adversely affects the ability of students to attend lectures and produce high quality
7 Putting on one side the effort required at Cambridge and Oxford, which dominate the tables for total student workload – it is remarkable how consistently those universities appear to require more effort of their students than other universities. On the other hand, they have fewer weeks in the academic year than other universities, so the extent to which this is so may be exaggerated by these results.

work 8 . Table 13 provides some support for that view but indicates that the impact of term-term working upon first and second year students’ academic activity is relatively small and largely confined to private study.
19.
It does appear, however, that term-time working has an impact upon students’ perception of value for money 9 , which suggests that satisfying students who are obliged to earn the money which finances their study will be a challenge for institutions as this becomes more common in future.
Table 13: Various indicators of students’ academic activity by hours of paid employment (results weighted to offset subjects of study)
Paid employment
None
1 to 5 hours
6 to 10 hours
11 to 20 hours
21 hours and more
All respondents
Hours of private study
13.5
13.1
12.8
12.4
11.6
13.1
scheduled hours not attended
(per cent)
8
8
8
8
10
8
Number of assignments submitted
10.4
10.1
9.9
9.7
Percentage reporting poor value for money
14
18
19
22
9.8
10.2
21
16
Satisfaction
Performance versus expectations
20.
The National Student Survey (NSS) provides a comprehensive review of the satisfaction of students and its findings are broadly supported by this survey. Table 14 shows that students display high levels of general satisfaction, with only 11 per cent reporting a worse that expected experience. However, adding those whose experience has been "worse in some ways" raises the figure rises to 51%.
Table 14: Has the reality of your experience matched your expectations?
Response
Yes, broadly
It's been better
It's been worse
Better in some ways, worse in others
Proportion of known
22%
26%
11%
40%
21.
Whilst only one student in nine considered their overall experience to be worse than expected, half considered some aspects to be worse
8 “Survey of higher education students’ attitudes to debt and term-time working and their impact on
attainment” A report to Universities UK and HEFCE by the Centre for Higher Education Research and
Information (CHERI) and London South Bank University
9 Students were asked if they thought their course represented good value for money. As is elaborated in the full report, there were significantly different responses to this question, depending on the characteristics of the respondent.

than expected. Amongst that group, disappointment with academic provision was much stronger than disappointment with other aspects of the university experience. This does not mean that academic experiences were generally poor – less than a quarter were dissatisfied with them – but it does suggest that investment in academic teaching remains critical to improving further what are generally strong levels of satisfaction.
22.
Table 15, below, shows that nearly one in five of those students reporting some disappointment with their experience thought that their university's prospectus had been misleading. This mismatch between what universities claim and the reality is something to which universities will need to pay attention. It suggests that universities may be misselling themselves in the eyes of significant numbers of students.
Table 15: If your experience has been worse than you expected, or worse in some ways, why do you feel this?
Response
For academic reasons
For personal reasons
University facilities don't match prospectus
Prospectus misleading in other ways
Other
All respondents
Proportion of known
41%
28%
10%
8%
13%
100%
23.
Overseas students were particularly likely to report that the university prospectus had given a false impression as is evident in figure
16. This is of concern because these students are not in a good position to assess claims made by English universities and because any hint that mis-selling is common amongst some English institutions is likely to affect the ability of all English institutions to recruit from overseas.

Figure 16: Reasons why experience was worse, or worse in some ways, by nationality
Academic reasons
UK
Personal reasons
EU
Other
Facilities don't match prospectus
Prospectus misleading in other ways
Other
0% 10% 20% 30% 40%
% of respondents
50% 60%
Perceptions of value for money
24.
As figure 17 (below) shows, three times as many international students thought that their course represented very poor value for money than home and EU students, and nearly 30 per cent of all international students thought that their course was poor value
(combining "poor value" and "very poor value"). On one level, the higher level of dissatisfaction is unsurprising – students from outside the
EU pay more and so the threshold for ‘good value’ will necessarily be higher. However, many universities are highly dependent upon their fees 10 , and it is worrying that such a high proportion of these students were dissatisfied.
10 See HEPI (2006) How exposed are universities to reductions in demand from international students www.hepi.ac.uk

Figure 17: Percentage of students perceiving poor value for money by nationality
30%
Poor value for money
25%
Very poor value for money
20%
15%
10%
5%
0%
UK EU
Nationality
Other