This survey summarizes the thoughts of 181 UK students ages 16-19 on their future choices after school or college. Most respondents intend to attend university (78%) and feel most informed about this option. Starting a business is the option students feel least informed about. The top career interests are science, medicine, and business. Over 40% felt their career choice was something they had always wanted to do rather than being influenced by others. Students said they would use websites most to research options but felt grants being cut would not impact their decisions much. Being happy was rated the top factor for success by many respondents.

1. Future choices:
A look at decisions, influence and motivations of young
people deciding what to do after school or college
December 2015

2. 1
CONTENTS
Executive Summary ............................................................................................................2
Methodology ......................................................................................................................3
Overview.........................................................................................................................3
Sample ............................................................................................................................3
Survey Design .................................................................................................................3
Data Analysis...................................................................................................................4
Response.........................................................................................................................4
Results ................................................................................................................................5
Single Variant..................................................................................................................5
Multivariate analysis.....................................................................................................14
Age............................................................................................................................14
Gender......................................................................................................................16
Domicile....................................................................................................................19
Career and other variables .......................................................................................19
Summary...........................................................................................................................23
Appendices .......................................................................................................................24
Appendix one................................................................................................................24
Appendix Two...............................................................................................................25

3. 2
EXECUTIVE SUMMARY
This report details the thoughts of young people in the UK as they consider what to do after leaving
school. Feedback was gathered in early September 2015 for those returning to a new school term. The
information represents a cross-section of thoughts and opinions and is not representative of the
general population.
There was a keen interest in going to university and this interest was equal for both male and female
respondents. On further investigation, it appeared that males had a higher certainty of going to
university aged 16 years of age compared to females. Female participants appeared to be less certain
of going to university at age 16 years and increase in certainty (Page 16). The female trend was
stronger than the male trend.
Respondents felt most informed about going to university and least about starting their own business,
as future options. They were more likely to state that their decision on future choices was based on
something they had always wanted to do rather than an external influence (Page 11).
A heartening discovery was the number who rated “Being happy with yourself” as the main success
factor for the future. There was an opportunity for free text at the end of the survey and many
respondents gave comment on the importance of happiness and being true to yourself as ambition for
the future (Page 12).
Acknowledgements to facilitators of The Spartan Test for organising the dispatch of the survey and to
the participants for their candid and often inspired feedback.
Debbie Scott
Managing Director
Spark and Bangle

4. 3
METHODOLOGY
OVERVIEW
In order to understand more about future choices made by 16 to 18 year old UK school pupils, a
survey was commissioned to ask key questions on their interest in career sectors, post-school options
and what motivates these choices.
The survey was created on-line and emailed to UK school pupils whom had registered on SACU-
Student1
website and in particular, registered to use the Spartan Test to discover suitable careers. The
Spartan Test is an image based quiz designed to help users refine potential career or academic
options.
SAMPLE
The sample chosen was in essence a census; incorporating the majority of registrants whom had
opted-in to receive email communications and who lived in England. Scotland, Wales and Northern
Ireland results were suppressed due to low registration or completion rates in case they compromised
the anonymity of respondents. The survey was designed for participants aged 16 years and older, in
accordance with MRS guidelines.
It was accepted that there would be inherent sample and selection bias and this is highlighted within
the survey design.
SURVEY DESIGN
The research was exploratory in design, there were no prior assumptions of hypothesis. Data was
collected using an online survey. There was no screening question since the survey related to all
future options open to young people of school age.
The possible answers to questions were randomised per individual respondent to prevent first choice
answering. Where scales were used, they were generally 4 point scales with two positive and two
negative options. Most questions were single choice, where relevant there were options to hit “other”
and provide more information. There was a final free text option where respondents could write
whatever they liked regarding future choices.
There was expected bias within the survey results.
Selection bias:
 It was expected more females would take part than males, as with other surveys.
1
www.sacu-student.com

5. 4
 It is possible that potential participants more certain of their future would agree to take part
in a survey entitled “future options” compared to those who are less certain. This was a
compromise between gaining informed consent and avoiding selection bias.
Sample bias:
 It was expected there would be a greater interest in “going to university” as a future choice
since the distribution of the Spartan Test is with schools more likely to send pupils to Higher
Education.
There was no mitigation against bias in the sampling and survey design. The findings are for general
insight into a small cross-section and are not being used to represent the national population nor as a
response to a specific research objective.
The survey completion was incentivised with prize draw entry to win a 1 of 3 vouchers valued £50 and
£25. Incentives used were vouchers redeemable at a number of shopping outlets that appeal to both
male and female consumers.
DATA ANALYSIS
The data was analysed in Microsoft Excel through pivot tables. The data was not factored against
national population statistics however the data was weighted on occasion to improve distribution
across categories where there where large skews. This was usually to weight male/ female categories
or age categories. The majority of results are unweighted and where results have been weighted, they
are clearly labelled.
Where it looked like there might be emerging trends in the responses, a range of significant tests such
as Chi-square and R-square to determine the strength of a trend. It is clearly labelled when tests have
been applied.
RESPONSE
In total 4,649 were emailed with an open rate average of 34.48% and click through rates of 6%. There
were initially 198 started surveys. Bogus and partially completed surveys (less than 25% complete)
were suppressed from analysis. The final respondent number that could be analysed was 181.
N = 4,649
n = 181

6. 5
RESULTS
The following pages detail highlights key findings from single and bivariate analysis.
SINGLE VARIANT
As predicted there was a considerably larger completion rate from females (71%) than males (29%).
There was an option for respondents to choose “Prefer not say” regarding gender though this was
rarely used. Since this option was only taken up by a small number of respondents, the response was
excluded to prevent any possible identification.
The age categories present were 17 years (83%), 16 years (11%), 18 years (4%) and 19 years or older
(2%).
0%
20%
40%
60%
80%
100%
16 years 17 years 18 years 19 years or
older
Respondent age
Figure 1: Pie chart to show gender of
respondents (Base: all respondents, n = 181)
Figure 2: Bar chart to show age categories (Base: all
respondents, n = 181)
Figure 3: Bar chart of respondent domicile (categories (Base: all respondents, n = 181)
70.95%
29.05%
Gender
Female
Male
0%
5%
10%
15%
20%
25%
30%
EastMidlands
WestMidlands
EasternEngland
GreaterLondon
SouthWestEngland
SouthEastEngland
NorthWestEngland
Yorkshireand
Humberside
NorthEastEngland
Group1 Group2 Group3
Region or Country of UK
Total

7. 6
There were respondents from all across England with slight over representation from the South West
and West Midland regions.
Respondents were asked to pick what they were most likely to do after straight after school or college
and indicate just one choice. As predicted there was a significant interest in pursuing higher education
(78%). There was an “other” category in which students could give free text responses. The majority
stated “I don’t know” and were recoded into the “I have not made my mind up”. The remaining
“other” options could not be recoded into existing categories as related to re-taking taking
qualifications. This is shown in figure 5.
The respondents were then asked how well informed they felt about all the previous options. There
was no skip logic for those that indicated “have not made my mind up” since such respondents may
still have an opinion on how well informed they were on potential future options. Respondents felt
most informed about going to university (78.49% - fully informed) and least informed about starting
their own business (36.63% - totally uninformed). This is shown in figure 6.
The 4-point scale was then grouped into the two positive (Fully informed/informed) and negative
responses (Totally uninformed, Uninformed) giving an overall informed or uninformed rating.
“I wish I was told more in regards to taking a gap
year before higher education and starting my own
business.” Respondent in open question
Region or Country % respondent
South East England 24.44%
West Midlands 18.89%
South West England 17.78%
Greater London 13.89%
North East England 12.78%
Yorkshire and
Humberside
5.56%
East Midlands 3.33%
North West England 1.67%
Eastern England 1.11%
Figure 4: Table to show regions or country of domicile for respondents ranked by
frequency (Base: All respondents n=181)

8. 7
Figure 5: Bar chart to show intention after school or college (Base = 180)
[I wish I was told…] “The variety of pathways that
get you the end career option.”
Figure 6: Stacked bar chart of how informed respondents felt on future options (Base = 180)
0% 20% 40% 60% 80% 100%
Do a part-time degree course
Do an apprenticeship
Do an on-line Higher Education course
Go straight into a job
I have not made my mind up yet
Other (please specify)
Set up a business / become…
Study full time at a university or…
Take a gap year
Intention after school or college?
Total
0% 20% 40% 60% 80% 100%
Full time HE
Apprenticeship
Employment
Entrepreneur
On-line Course
Work based Learning
Part Time HE
Average
Levels of how informed students felt on what to
do straight after school or college
Fully informed Informed Uninformed Totally uninformed

9. 8
Figure 7: Stacked bar chart to show grouped respondent levels of feeling informed with
different post school options (base = 180)
The grouped results showed that nearly all respondents (99.42%) felt that they were informed about
going to university to some extent. Respondents also indicated that they felt informed on options for
apprenticeships (69.18%) and going into employment (59.30%). Respondents felt least informed on
starting own business/ Entrepreneur (79.65%), on-line courses (70.49%) and work based learning
(53.22%).
Respondents were asked to indicate the career sector they would most like to work in, this included
an “Other” category. It was expected that there might be a number of “Other” responses since the list
of career areas was abbreviated. The majority of the “Other” categories were coded and added in to
the main section. The remainder of the “Other” answers were very obscure and not itemised. The full
list of career sector interest can be found in appendix one.
Figure 8: Table to show the 5 most popular and least popular career sectors for respondents (base = 178)
0% 20% 40% 60% 80% 100%
Full time HE
Apprenticeship
Employment
Entrepreneur
On-line Course
Work based Learning
Part Time HE
Average
Levels of how informed students felt on what to
do straight after school or college (Grouped)
Informed Uninformed
Career Sector % Career sector %
Science / Scientist 10.67% Third sector (charity) < 2%
Medicine or Dentistry 9.55% Construction < 2%
Business and Management e8.99% Entrepreneur < 2%
Teaching 6.74%
Hairdresser
or beautician < 2%
Performing Arts 5.62% Professional Sports < 2%

10. 9
Respondents were asked what has most influenced their desired career sector. There were initially
eight potential response categories plus one “Other” category. The results from the “Other” category
were either coded into main answers or used to create new ones. These categories were grouped into
four larger influence groups.
Figure 9: Bar graph to show strongest influence on career sector (Base =178)
[I wish I was told…] “That not
everyone has to go to university
to become successful. I think
that real examples should be
used to show students that you
can still be successful even if
you do not go to uni.”
The majority of respondents felt that there was no single
external influence for the career they were most interested in, they felt they had always had an innate
Influence type %
No external
influence 42.35%
Cultural influence 17.65%
Educational
influence 15.88%
Family and
Friends 18.24%
Experiential
influence 5.88%
Figure 10: Table to show grouped
responses by type of influence (Base =
178)
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
Noone-Ihavealwayswantedto
Author/Book
TVorFilm
Celebrityorpublicfigure
Sportsperson
MusicianorBand
CareersAdvisor
Teacher
Familymember
Friend
Personalexperience
Subject
Workexperience
No
external
influence
Cultural Influence Educational
Influence
Family and Friends
influence
Experiential influence
Single strongest influence on future career sector
Total

11. 10
interest for a particular field (42.35%). The next most frequent choices were family member (17.65%),
teacher (14.12%) and TV or film (12.35%).
The grouped results showed a roughly equal score for cultural influence (17.65%) and family influence
(18.24%). Experiential influence was the least frequent to be cited at 5.88%. This group contained
influence factors such as work experience, discovering a passion for a particular subject or a personal
experience such as an experience of being taken care of by nurses.
A topical issue at the early conception of the survey was the newly elected Conservative financial
budget which saw the removal of maintenance grants for future students. Respondents were asked
how much they felt this change might affect their decision on future choices. The majority felt that
removal of maintenance grants would make no difference to them (41.81%), many had no idea what a
maintenance grant was (35.59%) however nearly 1 in 5 did feel it might deter them from Higher
Education (19.21%)
Figure 11: Bar chart to show impact of maintenance grant removal on future decisions (Base = 177)
Respondents were asked what sources they would use to find out more about their future options.
Unsurprisingly for the digital natives, the majority would go to a relevant website with 51% ‘very
likely’ and 44% ‘likely’ to use this information source. The sources least likely to be used were Trade
Press (21%), a brother/sister (36%) and a library (29%)
[Success to you is…] “Being comfortable in your own
skin, and creating a better world”
[Success to you is…] “Being exactly who I want to be
in my mind and no one else's idea”
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
No, I had no idea what
maintenance grants
were in the first place
No, it makes no
difference to me
Yes, I am less likely to
go to Higher Education
now.
Yes, I am more likely to
go to university now
Has the removal of maintenance grants had any impact on
you future choices?
Total

12. 11
Figure 12: clustered bar chart showing what information sources students are most likely to
use when researching future options (Base = 172)
The 4 point scale was
grouped to likely or
unlikely sources. In this
example respondents
were 94% likely to use a
relevant website.
Students were equally
likely to seek information
from a friend as a student
review.
The majority of
respondents wanted to
enter Higher Education so
there is no surprise that
speaking to a university
representative is a
popular option at 77%.
Figure 13: Stacked bar chart to show grouped results on information sources (base = 172)
0%
10%
20%
30%
40%
50%
60%
Information source most likely to be used
Very Likely Likely Unlikely Very Unlikely
0% 20% 40% 60% 80% 100%
Parent or Guardian
Sibling
Friend
Other Family
Forum (on-line)
Relevant Website
Library
Careers Advisor
Teacher
Professional Network
University Representative
Student Review
Trade Press
Information source most likely used
(Grouped)
Likely source Unlikely source

13. 12
Respondents were asked to rank important success factors from a choice of 10 statements and rank
them where 1 is most important and 10 is least important. Clearly respondents may have felt that
some elements were of equal importance, however they were forced to rank in an order. 47% of
respondents ranked “Being happy with yourself” as the most important statement (1) whilst 36% of
respondents ranked “Being popular” as the least important statement (10). This 10-point scale was
grouped into quartiles of 1-3 highest priority, 4-5 some priority, 6-7 lower priority and 8 – 10 least
priority.
Figure 14: Stacked bar chart of future importance (Base = 157)
“Being happy with yourself” was ranked highest by nearly all respondents, there was greater variation
of rank order for the other statements.
Respondents were then asked to define, in an open ended question, what they felt success meant to
them. The most frequently used word was ‘Happy’ at 47%
Figure 15: Text
cloud of most
frequent words
used in
response to
what success
meant to the
respondent
(Base = 43)
0% 20% 40% 60% 80% 100%
Being happy with yourself
Contributing to society
Being able to express yourself
Having a partner
Having a family
Being recognised as an expert
Taking care of something or someone
Discovering something new
Being wealthy
Being popular
Please rank what is most important to you in the
future? (grouped)
Highest Priority Some priority lower priority least priority

14. 13
Examples of responses to this question included:
“Be happy with what I am doing, while doing
something good for the society and myself”
“Being able to live independently - without reliance
on others - and what would make me happy. Ideally I
would be able to move freely between my interests
and have the time and opportunity to do various
things work related and also personal desires.”
“Being comfortable with myself and what I do.
Having all the possibilities for growth I have now
with the help of my parents.”
The survey ended with an open ended question asking what information they wish they had been
told. There were 104 responses and they varied greatly making coding responses difficult. This
highlighted the diverse needs of today’s student and the challenge in providing the right information.
Text Analysis showed “university” and “courses” as the most frequently used terms.
“Further information into other options outside of
going to University”
“More information about the university application
process and also knowledge on apprenticeships as I
feel like I don't know much about them at all.”
“I wish I was told that I could do what I wanted and
not looked down on by teachers or told by them that
I should do something with my brain (academic
path/career) as that was discouraging yet I wasn't
discouraged because it's my life”
Figure 16: Text cloud of responses from open ended question on what
information they wish they had been told (Base = 104)

15. 14
The responses were eventually categorised into 17 different themes. By far the largest theme was
“Life lessons” making up 21% of responses. These were statements from the students wishing they
were told they can change their mind or that following a passion is more important than a career. The
second most present theme was wanting to know more about university entrance (13%) from student
finance to writing personal statements to entrance exams. Another frequent theme was pathways,
nearly 7% wanted to know the best pathways to a dream job or preferred course.
Other recurring themes included wanting to know more about starting own business (3.85%),
alternatives to HE (5.77%), gap years (2.88%) and apprenticeships (1.92%). 3.85% of respondents felt
they did not require any further information and indicated ‘Nothing’ as a response. The full table of
themes and examples can be found in appendix two
MULTIVARIATE ANALYSIS
The following results are a look at cross tabs of different data points in the results.
AGE
The age categories were not evenly distributed and there was a larger skew of 17 years olds (83%)
across the data set, with only 11% being 16 years, 4% being 18 years old and just 2% who indicated
they were 19 years and older. This was expected as the survey was sent to a mainly Year 12 audience.
When looking at age comparisons it was largely only viable between 16 years (11%) and 17 years old
(83%) for certain questions with high completion.
Where age appeared to have no effect:
There were several questions where age appeared to have no effect on the response. The removal of
the maintenance grants was not affected by age as 80% of 16 year olds and 78% of 17 years felt the
removal made no difference to them.
Age had no discernable impact on preferred career or how informed students felt about future
options. 17 years olds were more likely to respond with the “fully informed” answer then 16 years
olds however when looking at a grouped response as either informed or uninformed, the overall
scores were similar.
Where age appeared to have an effect
Age appeared to have an impact on what respondents wanted to do after straight after school or
college. 81% of 17 year olds indicated they were likely to go to university compared to 60% of 16 year
olds. Chi-Squared was applied on the nominal data which indicated there was a significance between
age and feeling decided whether to go to university.
Age also appeared to have an impact on what were indicated as most important factors in the future.
Both 16 years old and 17 years old respondents indicate “Being happy” as the most important factor
for the future. However it was much more frequently cited by 17 year olds (51.56%) compared to 16
year olds (27.78%). The factor “Being wealthy” was on the surface more frequently rated as
important by 16 years olds (17.65%) compared to only 2.99% of 17 year olds. There was a larger

16. 15
standard deviation for 16 years old respondents with many choosing 1st
or 10th
place for a factor.
There seemed to be greater difference of opinion amongst the 16 year old respondents and more
consistency with 17 years old respondents. “Being recognised as an expert” (8.00%) and “being able
to express yourself” (6.98%) were only ranked most important by 17 year olds and were not ranked in
first position at all by 16 year old respondents
Figure 17: Bar chart to show rank 1 most important factors for the future for 16 and 17 year old respond (Base = 157)
There was a difference in information source used to review future options across the ages,
particularly for those decided on entering higher education. The use of relevant website as an
information source remained the top choice. 16 year olds were more likely to say they would read a
student review compared to older ages, whereas interest in on-line forums increased steadily from 16
years through to 18 years.
Figure 18: Line chart to show which digital information sources are used by age
0% 10% 20% 30% 40% 50% 60%
Being happy with yourself
Being wealthy
Having a family
Taking care of something or someone
Being recognised as an expert
Having a partner
Being able to express yourself
Contributing to society
Discovering something new
Being popular
Rank 1 = most important factor
17 years 16 years
0%
20%
40%
60%
80%
100%
16 years 17 years 18 years
Line chart to show digital information source used for those
decided on going to Higher Education (grouped, base =172)
(HE specific) Relevant website (HE specific) An on-line forum (HE specific) Read a student review

17. 16
GENDER
There was a large skew in respondent completion with 71% completed by females compared with
29% males.
Where gender appeared to have no effect:
Gender appeared to have no effect on what students wanted to do straight after school or college or
on how well informed respondents felt about post school options. 78% of females and 77% of males
indicated they were most likely to go to university straight after school or college.
The results showed an equal interest in going to Higher Education between males (77%) and females
(78%) however it is a very different story when it comes to actually applying to Higher Education.
UCAS statistics have reported on the growing gap between male and female application rates over the
last five years. In 2014, 62,0002
more women were placed at university compared to men and 2015
UCAS analysis3
shows 18 year old women are 35% more likely to go to HE then 18 year old men. It is
therefore surprising to see the results which show an equal interest. Further investigation into age
and gender showed a linear trend. Males were likely to be more certain about going to HE at age 16
years and then decline in interest at 18 years, whereas females were less likely to be certain of going
to HE aged 16 years and increase in certainty.
The R squared value for the female linear trend was stronger (0.585) compared to the male linear
trend value (0.382) on unweighted values. It would be very interesting to re-run this with a larger and
more evenly distributed sample to see if this a repeated trend.
It initially appeared that there was a difference between males and females on the impact of removal
of grants, with female respondents appearing more affected. 52% of males said it made no difference
to their plans compared to 38% of females. 22% of females said the removal of the cap could deter
2
https://www.ucas.com/sites/default/files/28-aug-sex-all-ex-x1.pdf
3
https://www.ucas.com/sites/default/files/eoc-report-2015.pdf
0%
20%
40%
60%
80%
100%
16 Year 17 Years 18 years
Column chart to show intention to go university by gender and age
(unweighted)
Male Female Linear (Male ) Linear (Female )
Figure 19 Column chart to show intention to go university by variables

18. 17
them from going to university compared to only 12% of males. However a chiSq analysis was run and
there was no significance in the results.
Where gender appeared to have an effect
Gender did appear to have an impact on preferred career sector with responses following broad
gender stereotypes. Males were more likely to indicate Engineering, Finance, IT, Science and Armed
forces compared to females. Females were more likely to indicate Veterinary Science, Journalism,
Law, and Nursing, Psychology /counselling and social work.
Figure 20: Bar chart to show impact of gender on future career choices (Base = 178)
0% 2% 4% 6% 8% 10% 12% 14% 16% 18%
Architecture
Armed forces
Business and Management
Construction
Design
Engineering
Entrepreneur
Fashion
Film and media production
Finance and accounting
Hairdresser or beautician
IT and Technology
Journalism
Law
Marketing and advertising
Medicine and dentistry
Musician
Not sure
Nursing
Other
Performing arts
Physiotherapy
Police
Politics
Professional sports person
Psychology or counselling
Scientist
Social Work
Teaching
Third Sector (Charity)
Veterinary and animal science
(blank)
Male
Female

19. 18
61.36%
38.63%
Having a family: Male
Higher priority Lower priority
45.95%
54.05%
Having a family: Female
Higher priority Lower priority
The most important factors for the future appeared to vary by gender. The results of the 10-point
scale were grouped by rank 1-5 as important and 6 – 10 as lower importance to give two possible
positive or negative options. Three statements were given equal weighting by males and females.
These included: “Being happy” which was ranked most important (81% female, 82% male),
“Contributing to society” (60% female, 57% male) “Being recognised as an expert” (43% female, 38%
Male) and “Being popular” which was ranked least important (18% female, 22% male).
The factors that males were more likely to rank as higher importance than females included “Being
Wealthy” (59% male compared to 41% high importance female) , “Having a partner” (63% male
compared to 54% female) and “Having a family” (61% male compared to 46% female)
The factors that females were more likely to rank higher than males included “Discovering something
new” (50% female compared to 32% of males), “Being able to express yourself” (67% female, 51%
male) and “Taking care of something or someone” (49% female, 33% male)
Figure 21: Pie charts to show male / female rankings "Being Wealthy" (Base = 157)
Figure 22: Pie charts to show Male/female rankings "Having a family" (Base = 157)
58.69%
41.31%
Being wealthy: Male
Higher priority Lower priority
41.23%
58.77%
Being wealthy: Female
Higher priority Lower priority

20. 19
Figure 23: Pie charts to show male / female rankings of "Being able to express yourself" (Base = 157)
DOMICILE
Multivariate analysis was performed initially looking at all regional and country domiciles and then by
grouping regions into Midlands, Southern and Northern England. It was found that domicile had little
effect as a variable on many responses. Further analysis on geographic location is being conducted.
CAREER AND OTHER VARIABLES
The results of the preferred career sectors were compared to other question dimensions such as most
important influence and most important success factor in the future.
Career sector by top influence showed that respondents wanting to be teachers were more likely to
have been influenced by a teacher, those wanting a career in finance and accounting are more likely
to be influenced by a parent or guardian. The responses were grouped into four subgroups: cultural
(author, TV, sports person and musician), educational (Teacher or career advisor), no one (not
grouped) and experiential (work experience, personal experience, enjoying a subject). The results are
shown in figure 24.
Influence was compared with what a respondent wanted to do straight after school and college. The
majority felt there had been no influence (38.5%) on their choice. There was a nearly equal
distribution against other influence factors for cultural (19.25%), educational (17.04%) and family and
friends (18.52%).
66.67%
33.33%
Being able to express yourself:
Female
Higher priority Lower priority
51.07%
48.93%
Being able to express yourself:
Male
Higher priority Lower priority

21. 20
Figure 24: Clustered bar chart to show influence factors by career choice (Base = 157)
Career choices were compared with the important future success factors. This revealed a broad trend with
those choosing caring professions (social work, teaching, third sector) being less interested in “Being
wealthy” and ranking “Taking care of someone” or “Contributing to society” as more important. Examples
are shown in figures 25 and 26.
Other key stand outs were those interested in working in the Police Force were more likely to rank “Being
happy with yourself” as lower importance. Those indicating armed forces, nursing or journalism were more
likely to rank “Being popular” as an important factor compared to those who had indicated other choices.
Those indicating preference for science were less likely to indicate “Being popular” as important. Those
interested in performing arts and journalism were more likely to score “Being able to express yourself” of
greater importance to those interested in engineering. Those who were interested in a career in finance
and accounting were less likely to indicate “Taking care of someone” as important.
0% 20% 40% 60% 80% 100%
Architecture
Armed forces
Business and Management
Design
Engineering
Fashion
Film and media production
Finance and accounting
IT and Technology
Journalism
Law
Marketing and advertising
Medicine and dentistry
Musician
Not sure
Nursing
Performing arts
Physiotherapy
Police
Politics
Psychology or counselling
Scientist
Social Work
Teaching
Third Sector (Charity)
Veterinary and animal science
Career sector compared to influence (grouped)
Experiential
No one - I have always wanted to
Family & friend
Educational
Culture

22. 21
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Architecture
Business and Management
Engineering
Film and media production
IT and Technology
Law
Medicine and dentistry
Nursing
Police
Psychology or counselling
Social Work
Third Sector (Charity)
The importance of "Being wealthy" compared with career choice
Higher Importance
Lower importance
Figure 25: Bar chart to show future success factor "Being wealthy" against future career choice (Base = 157)
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Architecture
Business and Management
Engineering
Film and media production
IT and Technology
Law
Medicine and dentistry
Nursing
Police
Psychology or counselling
Social Work
Third Sector (Charity)
The importance of "Being popular" compared with career choice
Higher Importance
Lower importance
Figure 26: Bar chart to show success factor "Being popular" against future career choice (Base = 157)

23. 22
It has been suggested that those studying certain subjects or interested in particular careers are more
likely to be negatively affected by removal of the grants. UK Parliament Statistics4
suggest those from
manual working backgrounds or on arts-based courses are more likely to use a maintenance grant
compared to other groups. The results from this survey show that a portion of those interested in
working in arts based sectors such as fashion (50%), performing arts (40%) or film and media (20%)
were less certain of pursuing a university placement following the removal of grants. However many
interested in other sectors also expressed uncertainty regarding the removal of grants. This included
medicine and dentistry (25%) and veterinary science (33%) which are all longer 5 year courses where
the overall cost is higher to the student. There was also some uncertainty for those interested in
working in caring professions such as nursing (25%), teaching (8%) and social work (25%). There were
some career areas where the converse was true and respondents indicated they were more likely to
consider university after the removal of grants. Those wanting to work in law (25%) or journalism
(16%) were more likely to indicate this.
4
http://www.parliament.uk/briefing-papers/sn01079.pdf
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Column chart to show whether the removal of the maintence grant has had
any impact on decision to go to HE against subject/career.
No idea/No difference
I am less likely to go to
Higher Education now.
I am more likely to go
to university now
Figure 27: Column chart to show impact of maintenance grant and future career sector (Base = 177)

24. 23
SUMMARY
This survey was exploratory and developed as a metaphysical dipping a toe in the water of opinion
rather than as a conclusive report. With a small sample, the margin of error for results is higher but
nevertheless, like any interesting insight, it has led to a number of further questions.
Why was overall interest in attending university and college equal for males and females in this survey
and yet actual application numbers to higher education differ greatly? Was this a random result
brought about by sample bias or does the changing interest by age and gender offer some clues to
what might happen? Is there a difference in the decision making process? Is there a change in
certainty through confidence on exam results?
The fact that many respondents felt they have always had a calling for a particular career sector is
interesting. Does this mean some young people have an innate sense of future direction or are some
simply less able to recognise when they have been influenced? Is this the results of increased
individualism?
It was no surprise that young people were most likely to use a relevant website as an information
source. The second most popular information source was parent, followed by teacher. Perhaps there
is subsequent follow up to ascertain why “careers advisor” was a lower down as an information
source for young people when they want information for future options.
There appeared to be correlation between how well informed students felt and how likely they were
to choose that option. This seems fairly obvious, you cannot make an informed decision on something
you know little about.
The fact that some respondents indicated they would be more likely to go to higher education after
the removal of maintenance grants and that those stating this were more likely to want to study law,
was an interesting outcome. Law has a reputation for elitism with many of the top 24 graduate
employing law firms still preferring graduates from Oxbridge (20%) and other Russell Group (51%)
institutions (Legal Week, 2014) 5
. Is there a connection?
Finally the number of respondents indicating they wished they were given more well-being and
‘happiness’ advice was interesting. We have an education system good at preparing students for
exams and coursework but how well does it prepare for life? Should well-being and the pursuit of
happiness be part of modern curriculum?
This has certainly been an interesting project and has helped shape some hypotheses and direction for
further study. There is further advanced statistical analysis being carried out on results at the present
time. Any reader interested in seeing findings or discussing implication of findings, please get in touch
via www.sparkandbangle.co.uk
5
http://www.legalweek.com/legal-week/analysis/2354461/the-oxbridge-conveyor-belt-
a-progress-report-on-law-firms-efforts-to-widen-the-graduate-recruitment-pool

25. 24
APPENDICES
APPENDIX ONE
Career Sector %
Architecture 2.25%
Armed forces <2%
Business and Management 8.99%
Construction <2%
Design <2%
Engineering 2.81%
Entrepreneur <2%
Fashion 2.25%
Film and media production 2.81%
Finance and accounting 5.06%
Hairdresser or beautician <2%
IT and Technology 2.81%
Journalism 3.37%
Law 4.49%
Marketing and advertising 2.81%
Medicine and dentistry 9.55%
Musician <2%
Not sure <2%
Nursing 2.25%
Other <2%
Performing arts 5.62%
Physiotherapy <2%
Police 2.81%
Politics 3.37%
Professional sports person <2%
Psychology or counselling 4.49%
Scientist 10.67%
Social Work 2.25%
Teaching 6.74%
Third Sector (Charity) <2%
Veterinary and animal science 3.37%

26. 25
APPENDIX TWO
Nearly there! Please tell us what you wish you were told about your future options.
(Open ended question)
Theme % Examples:
Life lessons 21.15% That not every decisions you make now defines you.
University
entrance
13.46% How to write a personal statement
Careers 11.54% More options of what i [SIC] could do in the future career wise
Course query 8.65% I would like to know more about obscure courses that might link
unexpectedly to my main areas of interest.
Pathways 6.73% The variety of pathways that get you the end career option.
Alternatives to
HE
5.77% Further information into other options outside of going to
University
Decision
Making
4.81% More advice for people who have no idea what they would like
to do in the future.
University life 4.81% More about what it's like to study and live at university
Nothing 3.85% Nothing that i [SIC] can think of
Start own
business
3.85% The skills needed to be a successful entrepreneur
Difficulty 2.88% The difficulty of receiving a job according to the course or
degree you gain
Gap Years 2.88% I want to hear more about gap years
Graduate info 2.88% Average amount of graduates succeeding onto the careers which
they wanted
Apprenticeships <2% Much more about apprenticeships and internships
Earlier
information
<2% I wish I was told at a younger age so I could of [SIC] worked
towards it in an easier matter.
Pros and cons <2% What all of the options are, how to pursue each option and the
pro's [SIC] and cons
Exploring
passion
<2% More help exploring talents and/or passions and relating them
to possible jobs