Future choices: A look at decisions, influence and motivations of young

people deciding what to do after school or college

December 2015

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

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

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

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

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 orolder

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%

East

Mid

lan

ds

Wes

t M

idla

nd

s

East

ern

En

glan

d

Gre

ater

Lo

nd

on

Sou

th W

est

Engl

and

Sou

th E

ast

Engl

and

No

rth

We

st E

ngl

and

York

shir

e a

nd

Hu

mb

ers

ide

No

rth

Eas

t En

glan

d

Group1 Group2 Group3

Region or Country of UK

Total

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)

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

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 e 8.99% Entrepreneur < 2%

Teaching 6.74% Hairdresser or beautician < 2%

Performing Arts 5.62% Professional Sports < 2%

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%

No

on

e -

I hav

e al

way

s w

ante

d t

o

Au

tho

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Bo

ok

TV o

r Fi

lm

Cel

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ub

lic f

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re

Spo

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son

Mu

sici

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and

Car

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Ad

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r

Teac

her

Fam

ily m

emb

er

Frie

nd

Pe

rso

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exp

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nce

Sub

ject

Wo

rk e

xper

ien

ce

Noexternalinfluence

Cultural Influence EducationalInfluence

Family and Friendsinfluence

Experiential influence

Single strongest influence on future career sector

Total

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 whatmaintenance grants

were in the first place

No, it makes nodifference to me

Yes, I am less likely togo to Higher Education

now.

Yes, I am more likely togo to university now

Has the removal of maintenance grants had any impact on you future choices?

Total

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

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

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)

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

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

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

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

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

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

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

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)

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 toHigher Education now.

I am more likely to goto university now

Figure 27: Column chart to show impact of maintenance grant and future career sector (Base = 177)

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

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%

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