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Extra-Curricular Activity
and the Transition from
Higher Education to Work: A
Survey of Graduates in the
United Kingdom
Guy Tchibozo, Louis Pasteur University of Strasbourg, France
Abstract
This paper focuses on the effects of extra-curricular activity on graduates’
transition from higher education to the labour market.The study is based on a
survey of 119 graduates conducted in 2004 in the UK.The data gathered cover
a large range of social and leisure activities that the graduates carried on while
students at their universities. Several aspects of their transitional process from
student to worker are also covered.Data were analysed by means of linear and
logistic regression models. Results show that extra-curricular activity has a
significant influence on the transition process. First, extra-curricular experience
gives access to better occupational status but lengthens the period of unemploy-
ment preceding the first job. Second, as compared with the most frequently
observed extra-curricular behaviour,two profiles could be distinguished:the one
better performing than average, and the other worse performing. Results suggest
extra-curricular strategies to better enable graduates’ effective transition to
work.
Introduction
The topic of this paper is the influence that students’ extra-curricular
non-market activities exert on their transition process to the labour
market.
More often than not, students are involved in two types of extra-
curricular activities while studying at university: employment to sustain
academic life, and leisure or social activities.
On the one hand, students may be employed while studying. These
students’ jobs may influence their future access to the labour market
Higher Education Quarterly, 0951–5224
Volume 61, No. 1, January 2007, pp 37–56
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd, 9600
Garsington Road, Oxford, OX4, 2DQ, UK and 350 Main Street, Malden, MA 02148,
USA.
(e.g. Light, 2001). Such jobs constitute ‘market activities’ and will not be
the topic addressed here. On the other hand, students may be involved in
social or leisure activities. Some examples of social activities include such
things as student union, childcare and helping disabled or drug-addicted
people. Sports, the arts and culture are examples of leisure activities.
Such social and leisure activities constitute non-market activities. This
paper addresses the influence of these extra-curricular non-market
activities on graduates’ later access to the labour market.
Extra-curricular activity is important because of its potential to rein-
force and market the outcomes of the education system. Any particular
involvement in a certain type of extra-curricular activity may influence
a graduate’s transition process to the labour market, for instance, by
speeding up or slowing down access to employment. Therefore, it is
essential that students and graduates understand the impact of extra-
curricular activity and appraise the role it may play in their strategies for
transition from higher education to employment.
Analysing the effects of extra-curricular activity is also important to
guidance services. As was stressed in a recent international report
(OECD, 2004, pp. 51–55), most guidance activities in higher education
concentrate on course choices and on psychological counselling to deal
with students’ emotional and study problems. However, as educational
institutions are faced with increasing competition for students and
resources, the labour market outcome of graduates is becoming a key
marketing argument. Therefore, as a contribution to developing know-
ledge on the process of transition from higher education to the labour
market, analysing the effects of extra-curricular activities is crucial to
guidance services and to their host institutions.
Research attention to date has been focused on the influence
of extra-curricular activity on college choice decision making (e.g.
DesJardins, Dundar and Hendel, 1999), academic achievement (e.g.
Gerber, 1996), personality and social behaviour (e.g. Eccles et al., 2003)
and alumni generosity (e.g. Tucker, 2004). Factors affecting participa-
tion in extra-curricular activities have also been studied (e.g. Gager,
Cooney and Call, 1999). In contrast, little attention has been paid to the
influence of extra-curricular activities on the outcome of the education-
to-work transition process. Eide and Ronan (2001) have shown that, in
the United States, participation in varsity sports may have positive effects
on earnings, although these effects may vary according to graduates’
ethnic background. But researchers have generally ignored the role of
other types of extra-curricular activities as well as the effects of these
activities on non-salary conditions of labour market entry (search dura-
38 Higher Education Quarterly
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
tion, job status, etc.) Therefore, this study should be of interest to readers
involved in higher education, especially students, guidance researchers
and practitioners, and educational administrators interested in rethink-
ing the place of extra-curricular activities in higher education.
This study is based on a survey of graduates in the UK. The paper
is divided into three sections. Section one presents the interpretative
framework. Section two is devoted to the methodology adopted. Section
three presents and comments upon the main results obtained.
Interpretative framework
Economic theory, especially statistical discrimination theory, posits that
employers pay particular attention to the non-market activities of job
applicants (Phelps, 1972; Arrow, 1973; Viscusi, 1980; Blau and Kahn,
1981; Ragan and Smith, 1982). Sattinger (1998) has given an idea of
how this works. On the one hand, some employers value the non-market
activities of job applicants. These employers consider that having been
involved in non-market activities is an indicator of an applicant’s respon-
sibility, citizenship and maturity which they think will be of advantage to
the firm. On the other hand, other employers consider that non-market
activities have a negative effect. The main concern of this second type
of employer amounts to excluding high turnover rate (‘high-quit-rate’)
candidates, because turnover is costly to firms (i.e. costs of finding and
training a replacement). Since the turnover propensity of an applicant
cannot be observed directly, these employers divide applicants into
two groups: a high-attrition-rate group and a low-attrition-rate group.
These employers negatively associate worker turnover with non-market
activities.Two reasons may explain this perspective. First, involvement in
family life or in leisure or social activities may indicate low professional
commitment resulting in low productivity and eventually firing. Second,
family and social life (e.g. responsibilities in non-profit organisations or
in politics) can expand or become more important to such an extent that
the employee resigns from the firm. In both cases, extraprofessional life
would appear to be a source of turnover. Consequently, applicants
considered as belonging to the high-attrition-rate group are faced with
stricter employment criteria, lower wages and fewer interviews, and may
therefore be excluded altogether from the recruitment process, even
when they are as qualified as other candidates.
The statistical discrimination theory is not but one of the multiple
ways to explain restricted access to employment. A lot of alternative
approaches have been developed, especially by labour economists, that
Students’ Extra-Curricular Activities 39
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
take into account such diverse determinants as employers’ preferences,
job-searchers’ strategies, the behaviour of labour market intermediaries,
economic structures or labour market public policies. But statistical
discrimination is of particular interest because it provides a framework
to interpret extra-curricular activities. Within this framework, students’
leisure and social activities can be interpreted as non-market activities,
which employers consider positively or negatively. In that respect, the
statistical discrimination approach helps us to better understand the
relationships that might be observed between extra-curricular activity
and labour market entry.
Method
This study uses data from a survey conducted in 2004. The survey was
designed within the Research Laboratory in Theoretical and Applied
Economics (Beta) at Louis Pasteur University of Strasbourg (France).
Associations, offices, and networks of alumni from higher education were
contacted in the UK and were requested to invite their members to
respond a questionnaire on the survey website.
The questionnaire had three parts. Part one focused on personal
details and education, part two on the respondents’ extra-curricular
non-market activities while students, and part three on their experiences
during the transition process from higher education to the labour
market. The transitional period was defined as the three years immedi-
ately following graduation.
One hundred nineteen individuals responded to the questionnaire.
These respondents constitute the sample of the study. This is clearly a
small sample, although large enough to allow statistical treatment.
Sixty-one per cent of the respondents were women and 39 per cent
were men. Ages ranged from 22 to 59, but the average age was 29.As can
be seen from the first column of Table 1, 80 per cent were British citizens
but thirteen nationalities were represented.
Most respondents (66 per cent) held a bachelor’s degree, 27 per cent
a master’s degree and 7 per cent a doctorate. As reported in the second
column of Table 1, many major fields of study were represented.
Most respondents (53.78 per cent) graduated between 1998 and
2000.The average age at graduation was 25.The year they graduated, the
respondents were generally (75.63 per cent) neither married nor living
with a partner. Only 6 per cent had dependent children. Most respon-
dents (53.78 per cent) engaged in extra-curricular non-market activities.
Among these, 29.68 per cent participated in sports, 26.56 per cent
40 Higher Education Quarterly
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
TABLE 1
Nationalities, fields of study, types of activities and economic activity sectors represented in the sample (NB.
The number of respondents is in parentheses)
Nationalities Study subjects Types of activities Economic activity sectors
Belgium (1) A. Mathematics and sciences (24) Sports (19) Business services for firms (16)
Canada (1) Biology/Biochemistry (2) Construction (5)
China (1) Chemistry/Pharmacy (6) Social sector (17) Culture, sport, leisure activities (3)
Denmark (1) Earth science (4) Care to animals (2) Education (16)
Finland (1) Health/Nursing (1) Child care or support (1) Electricity, gas and water supply (2)
France (5) Natural sciences (2) Disability (2) Environment (1)
Germany (8) Physics (6) Labour or student union (1) Extra-territorial organisations (1)
Greece (1) Mathematics/Statistics (3) Mentoring (2) Financial intermediation (10)
Jordan (1) B. Engineering and technology (17) Prevention of cruelty (1) Health and social work (6)
Kenya (1) Building (1) Public charities (1) Hotels and restaurants (5)
Malaysia (1) Computer science (6) Scouts (5) Manufacturing (10)
Thailand (1) Electricity (1) Social exclusion (2) Media (4)
United Kingdom (95) Electronics (3) Mining and quarrying (3)
Non-response (1) Information technology (4) Student association (12) Other community activities (5)
Mechanical engineering (2) Public administration, defence (7)
C. Social sciences (54) Culture and spirituality (11) Research and development (9)
Business related (16) Arts, culture, literature (7) Services for households (1)
Economics (4) Religion (4) Telecommunications (5)
Education (1) Transport (5)
Environment (1) Citizenship (4) Wholesale and retail trade (5)
Finance (2) Environment (1)
Geography (6) Political organisation (2)
Hotel management/Catering (1) Public safety (1)
International relations (1)
Management (3) Non-response (1)
Marketing (4)
Students’ Extra-Curricular Activities 41
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
TABLE 1 Continued
Nationalities Study subjects Types of activities Economic activity sectors
Social sciences/Sociology (4)
Political science, public
management (6)
Law related (5)
D. Arts, human & information
sciences (24)
Anthropology (1)
Arts/Music (4)
History (2)
Human sciences/Psychology (4)
Languages/Linguistics/Literature
(5)
Librarianship/Documentation/
Archivist (5)
Publishing (2)
Theology/Pastoral ministry (1)
42 Higher Education Quarterly
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
engaged in the social sector, 18.75 per cent participated in student
associations, 17.18 per cent were involved in cultural and spiritual activi-
ties, and 6.25 per cent in citizenship activities (third column of Table 1).
Participants were involved in the extra-curricular activities for three
years on average. While most were simple participants, 42 per cent
engaged at leadership level, on average, for two years and six months.
Most frequently, participants practised within non-profit associations
(39 per cent), but a lot of them also practised with friends (36 per cent),
solo (e.g. playing violin at home or jogging alone: 12.5 per cent), with
their families (6.25 per cent), or as clients of service suppliers (e.g. going
to the movies or to the theatre: 4.68 per cent).
After graduation, all respondents entered the labour market. At that
point, 41.17 per cent experienced unemployment for four months and
one week, on average, before getting their first jobs. However, all of them
found a job within the transitional period. Eighty-one per cent of them
got an open-ended contract right from the first job on. The average net
monthly wage in the first jobs was £1,270. Much diversity could be
observed in the employment sectors (fourth column of Table 1) and in
the countries where the graduates were hired: 21 countries among which
mainly the UK (76.47 per cent), Germany (5 per cent) and France (2.5
per cent). The average working time per week in these positions was
39 hours. Fifty-four per cent of the first jobs belonged to the category
of managerial occupations, 21.84 per cent were office employee occu-
pations, and 17.64 per cent were technical or lower supervisory
occupations. Four respondents were workmen and two belonged to the
category of employers, self-employed and own account workers. Forty-
seven per cent of the first jobs were located in large firms (more than 500
employees), 32.77 per cent were located in small and medium enter-
prises (between 20 and 500 employees), and 19.32 per cent in micro-
enterprises (fewer than 20 employees).
Sample representativeness
Although the respondents of this survey cannot be considered as strictly
representative of the whole population of higher education graduate
leavers in the United Kingdom, they are in many ways close to this
population. As for the postgraduate leavers, the statistics from the Higher
Education Statistics Agency (HESA) most frequently focus on those
who were UK domiciled, and only take into account the first six
months after graduation. The observation period and classifications
(programmes of study, qualifications, activity sectors) used in this study
Students’ Extra-Curricular Activities 43
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
differ from those of HESA, which does not allow strict comparability.
However, it can be observed that the sample meets some of the charac-
teristics of the postgraduate leavers population. For example, with ref-
erence to 2001 leavers (HESA, 2002), Table 2 shows such similarities.
TABLE 2
Comparison between the sample and the population of higher
education postgraduate leavers in the United Kingdom (2000–2001)
Comparison criteria (%) Population
(%)
Sample
(%)
of men 41.8 39
of graduates from other EU countries 13.5 14
of doctorate holders 11.44a7
of graduates who entered the labour market 88 100
of open-ended contracts 70 81
of jobs located within the UK 90.3 76.47
of managerial and professional occupations 66a54
of supervisors and technicians 23.68a17.64
Subjects
Business and administrative studies 12.89 13.55
Mathematical sciences 1.71 2.54
Languages 5.46 4.23
Librarianship and information science 2.99 4.23
Architecture, building and planning 2.27 0.84
Law 2.74 4.23
Physical sciences 10.23 11.86
Biological sciences 10.23 8.47
Subjects allied to medicine 3.46 0.84
Creative arts and design 6.02 3.36
Computer sciences 9.61 5.08
Engineering and technology 10.76 5.08
Social, economic and political studies 11.29 31.35
Activity sectors
Electricity, gas and water supply 1.06 1.68
International organisations and bodies 0.12 0.84
Private households with employed persons 0.04 0.84
Transport, storage and communication 3.12 4.20
Mining and quarrying 1.15 2.52
Trade/repair of motor vehicles and goods 2.83 4.20
Financial activities 6.86 8.40
Manufacturing 10.55 8.40
Other community, social and personal service activities 6.82 4.20
Construction 0.86 4.20
Hotels and restaurants 0.61 4.20
Health and social work 12.03 5.04
aAmong UK domiciled.
44 Higher Education Quarterly
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
The sample structure and diversity in disciplines and activity sectors are
comparable with that of the population. Other characteristics like the
average age at graduation time and singleness while studying or entering
the labour market are also representative.Wages reported are also in line
with salary estimates from the Association of Graduates Recruiters.
However, the doctorate holders are under-represented in the sample.
Next, the percentage of graduates in the labour market is lower in
HESA statistics than in the sample because of a considerably shorter
observation period, six months instead of three years. Besides, two
subjects (computer sciences and engineering and technology) are under-
represented in the sample. The results of this study should not be
generalised to disciplines that are missing in this sample (education,
medicine and dentistry, veterinary science, agriculture). National data
on extra-curricular activities are lacking.
Statistical methodology
The effects of extra-curricular activity were investigated by means of
regression analysis. Five explanatory variables were taken into account:
the involvement in extra-curricular activities, the type of activity, the time
spent in the activity, the intensity of the involvement and the context of
practice. In addition, the degree levels and subjects were included as
independent variables in the estimates too, in order to clearly make the
difference between their own effects and those of the five extra-curricular
factors mentioned above. Three degree levels (bachelor, master and
doctorate) and four degree subjects (see second column of Table 1) were
distinguished.
Given that different variables can yield similar effects because of
intercorrelations between variables, intercorrelations were checked. No
case of strong intercorrelation among the independent variables could be
observed.
The effects of these potential factors were investigated on five catego-
ries of dependent variables: job security, occupational status, access to
large firms, wages and unemployment. For each outcome variable,
several alternative specifications were used in order to avoid missing any
significant effect. It was also checked that these outcome variables were
uncorrelated.
Linear regression analysis (ordinary least squares) was used when the
dependent variables were quantitative while logistic regression analysis
was used when they were qualitative. A two-step estimation procedure
was adopted.The first step consisted in estimating the effects of involve-
Students’ Extra-Curricular Activities 45
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
ment within the whole sample. The second step consisted in estimating
the effects of all other factors put together within the group of respon-
dents with extra-curricular experience.
Results and comments
As can be seen from Table 3, extra-curricular experience has a twofold
influence on the outcome of the transitional process. On the one hand,
having been involved in extra-curricular activity creates an advantage in
terms of occupational status. As compared with graduates who were
involved in extra-curricular activities, those who did not participate were
almost three times more likely to begin their careers as office employees
rather than as managers. On the other hand, graduates without extra-
curricular experience had been unemployed for a significantly shorter
period of time before getting their first jobs.
These findings show that involvement in extra-curricular activities
makes a difference. Further investigations demonstrate that within the
group of the graduates who decided to be involved, the nature of the
extra-curricular experience matters (once controlled for the degree sub-
jects and degree levels).
Job security
Within the group of graduates with extra-curricular experience, 93.75
per cent obtained an open-ended employment contract before the end of
the transitional period (78.12 per cent right from the first job on.) As can
be seen from Table 4 (columns Y1A & Y1D) and Table 5 (columnY1C),
the most important factor favouring job security is participation in
cultural activities.
As compared with other respondents, those who participated in
cultural and spiritual activities were more likely to get open-ended
contracts. Conversely, three characteristics were strongly linked with job
insecurity. The first one has to do with the depth of the involvement.
Graduates who engaged in an activity for a long period of time or at
leadership level had fewer chances of getting open-ended contracts.
Additionally, participation in the social sector led to fixed-term rather
than open-ended contracts. Finally, the graduates who had practised
with their families or as clients were less likely to be employed under
open-ended contracts within the transitional period.
46 Higher Education Quarterly
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
TABLE 3
The effects of non-involvement once controlled for the degree levels and the degree subjects – logistic and
linear estimates (Omitted reference category: the graduates with extra-curricular experience)
A. Logistic estimates
Dependent variable Odds ratio Z-ratio Pseudo R2N
Probability
of getting an open-ended contract right from the first job on (Y1A) 1.38 0.70 0.04 119
of getting an open-ended contract within the first three years (Y1B) 0.25 -1.37 0.07 70
that jobs within the first three years are with fixed-term contracts (Y1D) 1.38 0.77 0.03 111
of reaching a managerial position right from the first job on (Y2A) 0.61 -1.25 0.04 118
of occupying a managerial position at the end of the period (Y2B) 0.73 -0.66 0.04 104
of reaching a managerial position at any time within the period (Y2C) 0.56 -1.23 0.05 111
that the first job might be a lower supervisory position (Y3A) 1.12 0.22 0.05 118
of occupying a lower supervisory position at the end of the period (Y3B) 1.03 0.05 0.07 97
that the first job might be an office employee position (Y4A) 2.76** 1.96 0.15 118
of occupying an office employee position at the end of the period (Y4B) 2.27 1.34 0.11 104
of joining a large firm right from the first job on (Y5A) 1.21 0.48 0.06 118
of joining a large firm before the end of the transitional period (Y5B) 0.87 -0.32 0.05 108
of unemployment before getting the first job (Y7A) 0.58 -1.34 0.03 115
of unemployment within the transitional period (Y7B) 1.19 0.44 0.03 117
B. Linear Estimates
Dependent variable Coefficient T-stat R2N
Time spent working under open-ended contracts (Y1C) -7.73 -0.92 0.04 112
Size of the firms where the graduates were first hired (Y5C) 0.09 0.63 0.07 118
Size of the firms where the graduates were working three years later (Y5D) -0.03 -0.23 0.06 104
Wages at the beginning of the 3-year period (Y6A) 57.11 0.31 0.07 115
Wages at the end of the 3-year period (Y6B) 64.96 0.32 0.09 101
Duration of unemployment before the first job (Y7C) -1.44* -1.91 0.07 115
Total duration of unemployment within the transitional period (Y7D) 0.78 0.74 0.05 117
Total time spent working within the transitional period (Y7E) 0.25 0.03 0.02 117
*** Significant at the 1% level; ** Significant at the 5% level; * Significant at the 10% level.
Students’ Extra-Curricular Activities 47
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
TABLE 4
The effects of the nature of the extra-curricular activity – odds ratios
of the logistic estimates (Z-ratios are in parentheses)
Probability of
getting an
open-ended
contract right
from the
first job on
Y1A
N=50
getting fixed-
term rather
than open-ended
contracts
within the
transitional
period
Y1D
N=51
getting a
managerial
position
right from
the first
job on
Y2A
N=50
being in a
managerial
position at
the end of
the transition
period
Y2B
N=39
Type of extra-curricular activity
(X1)
Student associations 0.24
(-1.26)
0.82
(-0.20)
0.40
(-0.89)
52.34e +03
(1.45)
Activities in the social sector 0.03**
(-2.36)
0.89
(-0.10)
0.35
(-1.06)
260.34
(1.44)
Citizenship activities – – – –
Culture and spirituality 18.83*
(1.69)
0.02**
(-2.15)
0.24
(-1.42)
3254.84
(1.31)
Sports: reference category –
omitted
Time spent in extra-curricular
activities (X2)
0.92***
(-3.32)
1.03**
(2.04)
0.99
(-0.05)
0.78**
(-2.13)
Intensity of the involvement (X3)
Leadership level 0.14*
(-1.68)
1.22
(0.26)
4.19*
(1.68)
154.12**
(2.46)
Simple participant: ref.
category – omitted
Context of the practice (X4)
Solo 0.08
(-1.48)
0.85
(-0.15)
1.32
(0.27)
0.005
(-1.48)
With family 0.004**
(-2.35)
41.47**
(2.19)
9.82
(1.59)
12.20*
(1.87)
With friends 0.18
(-1.30)
2.58
(0.81)
2.46
(1.17)
166.48**
(2.11)
As clients of service suppliers – – – –
Within non-profit associations:
ref. category – omitted
Degree levels (X5)
Doctorate – – – –
Master’s degree 0.08*
(-1.95)
2.45
(1.08)
1.65
(0.70)
0.47
(-0.64)
Bachelor’s degree: reference
category – omitted
Degree subjects (X6)
Mathematics and sciences 0.05**
(-1.97)
2.99
(1.14)
0.82
(-0.22)
2.19e -04
(-1.50)
Engineering and technology – 2.70
(0.61)
––
Arts, human and information
sciences
0.003**
(-2.53)
10.52**
(2.16)
1.93
(0.87)
0.008
(-1.32)
Social sciences: reference
category – omitted
Pseudo-R20.44 0.25 0.12 0.56
*** Significant at the 1% level; ** significant at the 5% level; * significant at the 10% level.
48 Higher Education Quarterly
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
TABLE 4 Continued
reaching a
managerial
position
within the
transition
period
Y2C
N=38
occupying
alower
supervisory
position at the
end of the
transition
period
Y3B
N=25
beginning
one’s
career as
an office
employee
Y4A
N=46
working as
an office
employee
three years
later
Y4B
N=39
joining a
large firm
right
from the
first job
onY5A
N=57
joining
a large
firm
at some
moment
within
the period
Y5B
N=49
experiencing
unemployment
before the
first post-
Y7A
N=50
– – 13.35**
(2.0)
5.89e +14
(0.0)
17.55**
(2.44)
6.49*
(1.79)
0.57
(–0.56)
0.89
(-0.07)
1.60e -07***
(-3.10)
5.28
(1.29)
7.16e -72
(0.00)
8.31*
(1.92)
1.26
(0.24)
2.87
(1.01)
–– –– –––
0.13
(-1.05)
2.75e +04
(0.00)
21.58*
(1.78)
3.3e -58***
(–186.8)
20.08**
(2.23)
1.55
(0.34)
11.87**
(2.24)
0.91*
(-1.82)
1.21*
(1.95)
0.99
(-0.21)
1.5e +04
(0.00)
1.01
(1.31)
1.01
(0.65)
1.06**
(2.38)
675.96**
(2.27)
2.15e -22
(0.00)
0.24
(-1.35)
2.37e -86
(0.00)
0.57
(–0.69)
0.63
(–0.60)
0.15**
(–1.98)
3.41
(0.90)
– 0.43
(-0.51)
8.9e +75***
(59.9)
2.36
(0.69)
1.34
(0.25)
0.76
(–0.28)
132.53**
(2.03)
– – 2.91e +73
(0.00)
8.52
(1.14)
5.15
(1.18)
–
114.83*
(1.76)
5.02e -15
(0.00)
0.72
(-0.25)
4.08e +12***
(7.12)
0.85
(–0.17)
3.07
(1.22)
4.15
(1.43)
– – – 2.09e -08
(0.00)
3.72e +08
(0.0)
–
– – – – 9.1e +07***
(9.8)
3.0e -09***
(–11.3)
–
1.36
(0.27)
17.98
(0.91)
0.48
(-0.51)
5.14e -122
(0.00)
0.41
(–1.17)
0.85
(–0.19)
1.89
(0.72)
0.01**
(-2.31)
4.02e +27***
(12.8)
0.19
(-1.03)
1.46e +162
(0.00)
0.55
(–0.57)
0.64
(–0.46)
1.86
(0.68)
– – – – 1.75
(0.46)
1.83
(0.48)
0.10
(–1.24)
1.25
(0.23)
2.73e +06***
(2.72)
0.23
(-1.40)
4.00e +63
(0.00)
0.30
(–1.17)
0.29
(–1.15)
0.45
(–0.83)
0.36 0.67 0.23 0.87 0.23 0.16 0.30
Students’ Extra-Curricular Activities 49
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
TABLE 5
The effects of the nature of the extra-curricular activity – coefficients
of the linear estimates (T-stats are in parentheses)
Time spent working
under open-ended
contracts
Y1C
N=56
Size of the
first firm
Y5C
N=61
Size of the firm
at the end of the
transition
period
Y5D
N=50
Type of extra-curricular activity (X1)
Student associations 13.19
(1.15)
0.43
(1.22)
0.69**
(1.99)
Activities in the social sector 31.59
(1.21)
0.37
(1.38)
0.11
(0.31)
Citizenship activities 20.48
(1.39)
0.68**
(2.42)
0.93**
(2.32)
Culture and spirituality 22.81*
(1.94)
0.49
(1.39)
0.27
(0.67)
Sports: reference category – omitted
Time spent in extra-curricular activities (X2) 0.25
(0.91)
0.004
(1.27)
6.27e – 04
(0.10)
Intensity of the involvement (X3)
Leadership level 1.53
(0.13)
-0.16
(-0.69)
-0.05
(-0.22)
Simple participant: ref. category – omitted
Context of the practice (X4)
Solo -7.55
(-0.37)
-0.09
(-0.19)
-0.44
(-0.95)
With family -10.34
(-0.63)
0.56
(1.44)
0.57
(1.38)
With friends -22.36
(-1.37)
-0.06
(-0.20)
0.26
(0.75)
As clients of service suppliers -97.37***
(-5.10)
-0.65
(-1.36)
0.62
(1.57)
Within non profit associations: ref.
category – omitted
Degree levels (X5)
Doctorate 51.86***
(3.34)
0.68
(1.34)
0.11
(0.21)
Master’s degree -9.45
(-0.86)
-0.13
(-0.53)
0.13
(0.47)
Bachelor’s degree: reference
category – omitted
Degree subjects (X6)
Mathematics and sciences -16.98
(-0.76)
-0.13
(-0.38)
-0.25
(-0.67)
Engineering and technology -14.50
(-1.02)
0.33
(1.26)
0.27
(0.93)
Arts, human and information sciences -21.55
(-1.59)
-0.34
(-1.18)
-0.06
(-0.21)
Social sciences: reference category –
omitted
Constant 29.96**
(2.25)
1.92***
(6.98)
2.01***
(3.81)
R20.27 0.25 0.28
*** Significant at the 1% level; ** Significant at the 5% level; * Significant at the 10% level.
50 Higher Education Quarterly
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
TABLE 5 Continued
First job wage
Y6A
N=60
Wage at the end of
the transition period
Y6B
N=49
Duration of
unemployment
preceding the first
job
Y7C
N=59
Duration of
unemployment
within the transition
period
Y7D
N=60
Total time spent
working throughout
the transition period
Y7E
N=61
-618.78**
(-2.17)
253.92
(0.33)
-1.83
(-0.92)
1.99
(1.08)
22.22
(1.50)
-572.12*
(-1.84)
-376.87
(-0.65)
0.72
(0.28)
3.84
(1.18)
41.81*
(1.83)
-50.01
(-0.08)
503.23
(0.65)
3.62
(1.35)
3.61
(1.13)
27.86**
(2.00)
-383.46
(-0.92)
-276.11
(-0.50)
3.43
(1.07)
4.39
(1.31)
20.96*
(1.87)
1.95
(0.35)
-2.59
(-0.23)
0.01
(0.67)
0.05
(1.14)
0.28
(1.05)
138.57
(0.60)
347.75
(0.89)
-1.65
(-1.23)
-3.21
(-1.48)
-2.80
(-0.28)
229.72
(0.45)
-136.87
(-0.19)
2.31
(0.68)
1.82
(0.55)
-6.87
(-0.41)
236.87
(0.54)
1198.75*
(1.66)
-4.70**
(-2.38)
-5.83*
(-1.73)
-2.63
(-0.15)
330.67
(1.26)
233.18
(0.45)
3.76**
(2.01)
2.46
(1.18)
-10.39
(-0.68)
-182.28
(-0.33)
760.57
(0.57)
1.08
(0.68)
-1.18
(-0.70)
-74.81***
(-2.69)
873.77
(1.29)
713.34
(0.44)
-5.28**
(-2.06)
-2.55
(-1.05)
47.57***
(3.24)
306.61
(1.14)
404.04
(1.02)
1.47
(0.81)
2.63
(0.88)
0.10
(0.01)
-32.19
(-0.14)
-462.02
(-0.99)
2.18
(0.92)
0.57
(0.36)
-13.43
(-0.73)
780.22**
(1.96)
310.04
(0.53)
-1.42
(-0.72)
-1.05
(-0.61)
-24.36*
(-1.70)
181.87
(0.62)
-464.63
(-0.96)
-1.01
(-0.65)
1.61
(0.62)
-12.68
(-0.83)
1621.9***
(4.55)
2197.63***
(3.18)
0.30
(0.09)
-2.50
(-0.63)
24.69**
(2.41)
0.26 0.24 0.25 0.24 0.22
Students’ Extra-Curricular Activities 51
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
Occupational status
Of the respondents with extra-curricular experience, 71.87 per cent
reached a managerial position within the transitional period (59.37 per
cent right from the first contract on). As can be seen from the second
part of Table 4 (columns Y2A to Y4B), the access to a managerial
position mainly depends on the depth and length of the involvement in
activities as well as of the context of practice. A leadership experience
gives more chances of reaching managerial positions. However, the
whole extra-curricular experience should be kept in reasonable limits:
the longer the experience, the fewer the chances of reaching managerial
positions. Practice with family or with friends is also significantly corre-
lated with becoming a manager. The types of activity play a role too.
Although no type of extra-curricular activity gives particular chances of
becoming a manager, it seems that participation in student associations
or in cultural activities are especially inadequate and tend to shift the
graduates towards lower supervisory or office employee positions, at least
for the first jobs.
Access to large firms
Of the respondents with extra-curricular experience, 51.56 per cent were
employed in large firms during the transitional period (42.18 per cent
right from the first job on).
Tables 4 (columns Y5A & Y5B) and 5 (Y5C & Y5D) show that
participation in sports was the less efficient extra-curricular activity as
regards beginning one’s career in a large firm. In comparison with
participation in sports, involvement in student associations, in the social
sector or in cultural activities gave better chances of joining a large firm
right from the first job on. Graduates with an experience in citizenship
activities also began their careers in larger firms. And at the end of the
transitional period, graduates who had been participating in student
associations or in citizenship activities were working in larger firms than
those who participated in sports. Only the type of activity seems to
matter. No other extra-curricular factor seems to have an influence on
the access to large firms.
Wa g e s
As reported in the third part of Table 5 (columnsY6A and Y6B), wages
are influenced by the context of practice and by the type of activity. Two
52 Higher Education Quarterly
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
observations may be made. The first one is that, as compared with
practice within associations, practice with family seems to be more
closely linked with better wages at the end of the transitional period.The
second observation is that the graduates who participated in student
associations or in the social sector had lower first-job wages than those
who participated in sports.
Unemployment
Fifty per cent of the respondent graduates with an extra-curricular
experience have been unemployed at some time within the transition
period (46.87 per cent before the first job.) As shown in the last parts of
Table 4 (column Y7A) and Table 5 (columns Y7C to Y7E), the risk and
length of unemployment depend on the four extra-curricular factors.
On one hand, two characteristics lower the risk and length of
unemployment. First, the graduates who had been leaders in their extra-
curricular activities had a lower risk of experiencing unemployment
before the first job. Second, as regards the length of unemployment, the
graduates who had practised their activity with their family were unem-
ployed during a significantly shorter period of time than others both
before and after the first job. On the other hand, some other character-
istics increase the risk and length of unemployment. First, participation
in cultural activities and long-term involvement increase the risk of
experiencing unemployment before the first job. Second, practice with
friend or as a client lengthens the spells of unemployment.
Extra-curricular profiles
It thus can be seen that within the group of graduates with an extra-
curricular experience, the nature of the extra-curricular activity makes a
difference to entry into the workforce. Although most extra-curricular
factors have a twofold influence (e.g. experience in student associations
gives access to large firms but is correlated with low wages), three
clear-cut profiles could finally be distinguished.
Profile 1 comprises ‘Leaders and Citizens’. The graduates who
engaged at leadership level had better access to managerial positions and
the lowest risk of unemployment before the first job.Those who partici-
pated in citizenship activities had access to large firms right from the first
job on, and all along the transition period.Their spells in unemployment
also seem to have been shorter. Within the interpretative framework
presented in section 2, this means that most firms appreciated the
Students’ Extra-Curricular Activities 53
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
graduates’ extra-curricular experience as leaders or in citizenship activi-
ties, and took it as a predictor of high productivity.
Profile 2 represents the ‘Sportspersons’. This profile corresponds to
the most frequent extra-curricular behaviour, which consists in practic-
ing sports as simple participant within associations. Profile 2 appears to
be generally associated with average transition outcomes.
Profile 3 comprises ‘Activists and Clients’. This profile features long-
term participation and practice as a client. It could be observed that the
graduates who practised for a long period or as clients had fewer chances
of getting open-ended contracts or managerial positions, and were at
more risk of unemployment. According to the interpretative framework
of this paper, this means that most employers considered long-term
extra-curricular involvement and practice as a client as predictors of low
professional commitment, low productivity, and high risk of turnover
either by firing or by quitting.
Conclusion
The objective of this research was to investigate the influence of students’
extra-curricular activities on their transition into the labour force. The
interpretative framework provided by the approach of statistical discrimi-
nation suggests that extra-curricular activity may be viewed as a
determinant of productivity and therefore influences the employment
decision.
Five remarks can be made about the influence of extra-curricular
activity. First, statistically significant relationships between extra-
curricular activity and the transition process were observed. Second,
extra-curricular experience in itself makes a difference. As compared
with the graduates who were involved in extra-curricular activities, those
who were not [involved] have been more likely to reach lower occupa-
tional statuses although they were also unemployed for a shorter period
of time before getting their first jobs.The third remark is that, within the
group of graduates with an extra-curricular experience, the nature of
the experience matters. According to the degree of involvement in and
the type, length and context of the extra-curricular activity, the effects of
activity on the transitional process can be significantly different. Fourth,
it appears that, in the population studied, extra-curricular experience
influences all dimensions of the transition process.
Finally, three clear-cut extra-curricular profiles could be observed.
The ‘Leaders and Citizens’ (experience in citizenship activities or as
leaders), had the best transition outcomes (access to large firms and to
54 Higher Education Quarterly
©2007 The Author. Journal compilation ©2007 Blackwell Publishing Ltd.
managerial occupations, low risk of and short spells in unemployment).
The ‘Sportspersons’, the most frequently observed extra-curricular
behaviour, associated with average transition outcomes. Finally, the
‘Activists and Clients’ (long-term participation or practice as clients),
had the poorest transition outcomes (job insecurity, low occupational
statuses, high risk of unemployment).
These results emphasise the strategic potential of extra-curricular
activity for students and graduates wishing improved transition to the
labour market. Of course, extra-curricular activity is not only a matter
of career development. It surely has much to do with personal
development. But insofar as employers take account of the non-market
involvement of job applicants, neither students nor education and guid-
ance institutions should ignore the professional dimension of extra-
curricular activity.Thus, for instance, it might be suggested to graduates
to highlight in their resumes their ‘Profile 1’ features. Awareness of the
strategic potential of extra-curricular experience should also encourage
guidance institutions to survey employers’ extra-curricular preferences
at the local level in order to assist graduates in building university-
to-work transition strategies including effective extra-curricular
participation. Furthermore, reconsidering the position and recognition
of extra-curricular activities within higher education and their links with
regular curricula might be of advantage to educational institutions facing
competition in the higher education market.
However, these results also raise the question of the way employers
derive turnover and resignation probabilities from the nature of any
extra-curricular activity.Why should employers unanimously appreciate
involvement in citizenship activities but have diverging perspectives
regarding participation in the social sector or in cultural and spiritual
activities? A better understanding of employers’ rationale and prefer-
ences regarding extra-curricular experience surely calls for further
investigation.
Acknowledgements
Many thanks to Mrs Sylvie Maurer, to Dr Joseph Adwere-Boamah, to Dr
M’hamed Dif and to Professor Wade Nelson for their comments and
help.
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