International Journal for Research in Vocational Education and Training (IJRVET)
Vol. 5, Issue 4, December 2018, 264-284
DOI: 10.13152/IJRVET.5.4.2
Higher Education in Switzerland:
Predictors of Becoming Engaged in
Higher Vocational or Academic
Education – the Role of Workplace
Factors
Christof Na¨gele∗, Markus P. Neuenschwander, and Patsawee
Rodcharoen
University of Applied Sciences and Arts Northwestern Switzerland, School of Education,
Institute Research and Development, Centre for Learning and Socialisation,
Obere Sternengasse 7, 4502 Solothurn, Switzerland
Received: 25.06.2018; Accepted: 07.11.2018; Published: 17.12.2018
Abstract
Context: Vocational education and training enables young people to quickly and ef-
fectively enter the labour market. To advance their careers and to develop their pro-
fessional expertise even more, they must then further their education through higher
vocational or higher academic education. In this study, we looked at young people at
work: What motivates them to move on towards higher education? As they are engaged
in their jobs, their work situations will affect their further educational engagement. We
hypothesised that individuals will more likely move towards higher education if their
workplaces offer learning opportunities and social support. Human capacities, attitudes,
and goals at work develop mainly in informal or non-formal learning situations and in
their interactions with their teams. We tested the effect of these workplace factors by
taking into account additional important predictors of educational pathways, such as so-
ciodemographic factors (social background, nationality, gender) and motivational factors
(values).
∗Corresponding author: christof.naegele@fhnw.ch
ISSN: 2197-8646
http://www.ijrvet.net
Higher Education in Switzerland 265
Methods: Data stemmed from a multi-cohort longitudinal survey on educational deci-
sions and educational pathways in the German part of Switzerland (BEN), running from
2012 to 2016. The selected sample consisted of 601 working individuals who were not
engaged in higher education in 2014. Multinomial logistic regressions were run to test
the hypothesis.
Findings: First, we found that only 35% of the individuals who wanted to become en-
gaged in higher vocational education in 2012 became engaged up to 2016 compared with
those intending to become involved in higher academic education, where the rate varied
by age—from younger to older—between 45% and 70%. Second, we found distinctive
predictors for becoming engaged in higher vocational or academic education. Workplace
factors predict engagement in higher vocational education but not sociodemographic fac-
tors, whereas sociodemographic and not workplace factors predict engagement in higher
academic education. A significant predictor for both groups is the value attributed to
higher education.
Conclusions: The unique contribution of this paper is to show that distinct patterns of
becoming engaged in higher vocational or higher academic education exist. These results
confirmed the persistent effect of sociodemographic factors that shape the pathway to
higher academic education. Moreover, the results indicated that an individual’s value
and workplace factors contribute to enabling paths to higher vocational education, as
this depends not on sociodemographic factors but on shaping the work environment that
supports learning at work.
Keywords: VET, Vocational Education and Training, Lifelong Career, Professional
Development, Learning Culture, Social Inequality
1 Introduction
Further education and training is important for individuals as well as for companies
and society (Noe, Clarke, & Klein, 2014), and it is an essential aspect of developing a
meaningful work career (Duffy, Blustein, Diemer, & Autin, 2016). Although vocational
education and training enables young people to quickly and effectively enter the labour
market, a drawback of this early specialisation is the reduced adaptability to changing
occupational environments later (Hampf & Woessmann, 2016). Completing further edu-
cation after completing initial vocational education and training is therefore important,
as this helps an individual to advance his or her career, gain access to employment, and
sustain and develop the skills needed for innovation and sustainability in a changing and
competitive labour market. After graduating from vocational education, not all indi-
viduals pursue further education. Engagement in further education during a person’s
early professional career depends on a multitude of factors. Sometimes further educa-
tion is seen as being concurrent with productive work. It is the organisational learning
culture that enables incidental and non-formal learning at work (Marsick & Watkins,
2003), which also paves the way for formal education. Learning at work contributes to
an individual’s achievement and performance as well as to his or her future development
266 Na¨gele, Neuenschwander, Rodcharoen
(Janssens, Smet, Onghena, & Kyndt, 2017), as the boundaries between these modes of
learning overlap (Manuti, Pastore, Scardigno, Giancaspro, & Morciano, 2015).
Individual planning for further education depends on more than merely organisational
factors, such as the learning opportunities available at work. Rather, planning also
depends on educational opportunities within a specific educational system, as well as
on the social expectations and the particular context as reflected by an individual’s
origin, nationality, or gender (Becker, 2016). Furthermore, planning also depends on an
individual’s motivation to pursue higher education1 (Neuenschwander, Gerber, Frank, &
Rottermann, 2012; Wigfield, Rosenzweig, & Eccles, 2017).
Irrespective of the question of the educational system, the underlying question is,
why do some individuals continue their tertiary education on the vocational pathway
whereas others choose the academic pathway? Knowing why individuals follow either the
vocational or the academic track to higher education helps companies and counsellors to
better advise and coach individuals and to develop measures for upskilling and retaining
their workforces by allocating them to higher vocational education.
2 Predicting Participation in Higher Education
Here, we discuss how workplace-related factors, sociodemographic factors, and an indi-
vidual’s value towards further education shapes becoming engaged in higher vocational
or higher academic education.
2.1 Workplace Factors
The effects of the workplace on becoming engaged in formal education is complex (Van-
thournout, Kyndt, Gijbels, & Van den Bossche, 2015). Workplace factors affect an
individual’s personality, identity, and goals (Parker, 2014) and can offer opportunities
for growth and positive development. This eventually leads to a more self-directed ori-
entation, autonomy, and openness to experiences (Frese, Garst, & Fay, 2007), including
an orientation towards higher education. Overall, workplace learning has the power to
expand human capacities (Evans, Guile, & Harris, 2011).
The organisational learning culture is the background against which learning in a com-
pany is organised (Janssens et al., 2017; Kyndt & Baert, 2013; Messmann & Mulder,
2015) and whether the job design enables learning (Hackman & Oldham, 1975; Raem-
donck, Gijbels, & van Groen, 2014). Work offers incidental, informal, non-formal, or
formal learning opportunities that should be seen as interacting modes of learning and
not as discrete entities (La Belle, 1982). A company’s learning culture and an individual’s
abitlity to pro-actively take advantage of planned and emerging learning opportunities
(Billett, 2004; Illeris, 2003) help the individual to develop the knowledge and skills needed
1Higher education on the tertiary level is divided into higher vocational education and higher academic
education in Switzerland. See chapter on higher education in Switzerland in this paper.
Higher Education in Switzerland 267
to perform his or her job, and they also motivate individuals to develop future perspec-
tives with respect to their competence development and educational plans (Janssens
et al., 2017; Kraiger, Ford, & Salas, 1993). Positive learning experiences strengthen
self-efficacy beliefs and outcome expectations (Lent, Brown, & Hackett, 2002), and they
eventually nourish an individual’s desire and readiness to invest in further education.
In sum, work and task immanent learning opportunities allow an individual to advance
the knowledge and skills and the career (Dehnbostel, Elsholz, & Gillen, 2007; Stalder &
Carigiet Reinhard, 2014).
Hypothesis 1: Individuals are more likely to engage in higher education if they perceive
their learning opportunities at the workplace positively compared with those who work
without further formal education. Learning in the workplace is embedded in a social
situation. Colleagues and team members play a crucial role in shaping an individual’s
view of what has to be done and also on how things are done, through the development
of a shared understanding of career prospects within the team. In addition, learning at
work depends on the colleagues’ social support (Eraut, 2007; Lave, Chaiklin, & Lave,
1993), and impacts the reflection and definition of career goals and activities (Lent,
Ezeofor, Morrison, Penn, & Ireland, 2016; Wang & Fu, 2015). Social support helps
people to achieve their self-imposed career goals. On the one hand, social support can
foster career aspirations and development (Hofmann, Stalder, Tschan, & Ha¨feli, 2014).
On the other hand, it can hurt an individual’s career planning. As individuals become
members of a team (Lave & Wenger, 1991; Wenger, 2008), they also develop a mutual
feeling of belongingness and identify with the team and with their specific roles within
the team. Teams can develop an unwillingness to change the composition and role
distribution even if a change may be needed (Rafferty & Jimmieson, 2010). A team
member who is planning to complete higher education may spark conflict within the
team, as the team might not want to endanger its quality by allowing a team member
to move away to complete higher education. Social support is a valuable resource that
helps individuals to cope with workplace affordances (Frese, 1989). Taking into account
that individuals have a strong need of belongingness (Deci & Ryan, 2008), strong social
support could also hinder further higher education, primarily if it results in having to
leave the workgroup.
Hypothesis 2: Strong social support causes individuals to become less engaged in
higher education. Strong social support is like glue that binds the team members to-
gether.
2.2 Sociodemographic Factors
Much research shows that educational pathways depend on social origin, nationality, or
gender (Becker, 2016; Ion, Nye, & Iliescu, 2017; Lamamra, 2017). The social origin of
a family, as represented by the family’s socioeconomic status, was found to be one of
the major explanatory variables of educational pathways, whereby a higher socioeco-
nomic status is associated with higher educational expectations (Johnson & Reynolds,
2013; Neuenschwander et al., 2012). Social origin affects the transition from school
to education as well as the transition to higher education (Swiss Coordination Centre
268 Na¨gele, Neuenschwander, Rodcharoen
for Research in Education [SKBF CSRE], 2014). However, some evidence also indicates
that socioeconomic status does not affect a person’s decision to follow a higher vocational
pathway (Trede, 2016).
Hypothesis 3a: The higher a family’s socioeconomic status, the greater the chance
that a person in that family will complete higher academic education. We expected no
effect of socioeconomic status on completing higher vocational education.
It has been found that it is harder for individuals with migrant backgrounds to access
higher education. A significant effect of migration status is found in the transition to
upper-secondary education (Hupka-Brunner, Sacchi, & Stalder, 2010; Wolter & Zum-
buehl, 2017) and in the transition to tertiary education (Picot & Hou, 2013).
Hypothesis 3b. Swiss citizens are more likely to become engaged in higher education
compared with individuals with migrant backgrounds who are not Swiss citizens.
Gender stereotypes, gendered career expectations, and the socialisation process at
home, during compulsory school, during career orientation, and in initial vocational
education and training result in very persistent gender differences and inequalities in the
Swiss labour market (Hadjar & Aeschlimann, 2014; Lamamra, 2017). We see that many
young men choose vocational education and training at the upper secondary level even if
their school records would allow them to pursue general academic education.2 We expect
these young men to proceed towards higher education more often after graduating from
initial vocational education and training.
Hypothesis 3c: Men are more likely to participate in higher education than women
are after graduating from initial vocational education and training.
2.3 Value of Further Education
Motivational theories on career choices propose that educational values (attainment, in-
terest, utility) and expectations predict educational choices (Wigfield & Cambria, 2010;
Wigfield et al., 2017). Values represent the relative importance given to a specific ed-
ucational choice (Brown & Crace, 1996). If a person does not attribute high value to
higher education, little chance exists that this option will be chosen. We expected that
only individuals wanting to become engaged in higher education would become engaged
in higher education.
Hypothesis 4: The higher the value given to higher education, the more likely that
individuals be in higher education within two years.
The hypotheses are summarised in Figure 1.
2.4 Higher Education in Switzerland
As the hypotheses were tested based on a sample of young Swiss workers, it would
be helpful to describe higher education in Switzerland briefly. Tertiary education in
Switzerland features a two-tier structure: Higher vocational education is called profes-
sional education, and higher academic education is called university-based education.
2Numbers from the Federal Statistical Office, https://www.bfs.admin.ch/bfs/de/home/statistiken/bildung-
wissenschaft/bildungsindikatoren/bildungssystem-schweiz/themen/abschluesse/maturitaetsquote.html,
last accessed 16 February 2018.
Higher Education in Switzerland 269
Higher vocational education and higher academic education are at International Stan-
dard Classification of Education Level 6. In this paper, we focus on those who hold a
Federal VET Diploma after having completed initial vocational education and training.
Holders of Federal VET Diplomas have three pathways to proceed with their work and
educational pathways after graduation: 1) They can work and eventually attend some
non-formal, often short-term courses in continuing education and training, 2) they can
attend higher vocational education, or 3) they can attend higher academic education on
the condition of having baccalaureate degrees.
The vocational track is for most young people the standard pathway to a diploma at
the upper secondary level (Stalder & Na¨gele, 2011). According to data from the Federal
Statistical Office, in 2016, 63%3 of the diplomas issued were Federal VET Diplomas, and
15% acquired professional baccalaureates4 typically obtained during initial vocational
education and training or shortly afterwards. Holders of VET diplomas acquire diplomas
in higher vocational education either by passing a federal examination, based on self-
reliant preparation for the examination, by attending preparatory courses, leading to a
Federal Professional Education and Training (PET) diploma, or by enrolling in study
programs at colleges of higher education (Na¨gele & Bierschenk, 2014; State Secretariat
for Education Research and Innovation [SERI], 2016). Higher academic education is
accessible via a baccalaureate or after having completed a study program at a college
of higher education, and it is delivered via cantonal universities, federal institutes of
technology, cantonal or regional universities of applied sciences and arts, and universities
of teacher education.
Higher vocational education and higher academic education are positioned as different
educational pathways of equal value. Higher academic education is primarily financed
by the state, higher vocational education is primarily privately financed by the partici-
pants and the employers.5 According to the Federal Act on Vocational and Professional
Education and Training 6 and the State Secretary of Research and Innovation (SERI),
the aim of higher vocational education is to develop the competences needed to handle
challenging technical or managerial activities and to provide the labour market with
highly skilled workers (State Secretariat for Education Research and Innovation [SERI],
2016). An individual with a Federal VET Diploma as a carpenter, for example, can com-
plete higher vocational education to specialise in project management, the trade-specific
business economy, wood technology, etc. In higher academic education, the options for
the same individual are a bachelor’s and master’s degree in architecture or wood tech-
nology, a master’s degree in engineering, or many other bachelor’s and master’s courses
(Verband Schweizerischer Schreinermeister und Mo¨belfabrikanten [VSSM], 2017).
3https://www.bfs.admin.ch/bfs/en/home/statistics/education-science/diploma/upper-secondary.html,
last accessed 9 February 2018
4https://www.bfs.admin.ch/bfs/de/home/statistiken/bildung-wissenschaft/bildungsindikatoren/bild
ungssystem-schweiz/themen/abschluesse/maturitaetsquote.assetdetail.4282892.html, last accessed 9
February 2018
5Since January 2018 participants in higher vocational education can apply to get a refund from the state
for the preparatory courses, but not for the examination fee.
6https://www.admin.ch/opc/en/classified-compilation/20001860/index.html
270 Na¨gele, Neuenschwander, Rodcharoen
3 Method
3.1 Participants
Our data stemmed from two waves of a multi-cohort longitudinal questionnaire-based
survey on educational decisions and educational pathways (BEN), running from 2012
to 2016 in the German part of Switzerland (Neuenschwander, Du¨ggeli, Na¨gele, & Frey,
2017). The selected sample for the analysis consisted of individuals who took part in
the second and third waves of the study in 2014 and 2016.
Participants were either recruited through vocational schools (cohort one) or by send-
ing out letters to employers and directly to potential participants (cohort two). A
stratified random sample was obtained taking into account occupations and cantons.
Individuals from cohort one were close to the end of their initial vocational education
and training in 2014, whereas individuals from cohort two had been employed for a few
years after graduating from initial vocational education and training. Participants were
employed in various sectors, representing the most frequently chosen apprenticeships; for
example, they were commercial employees, retail clerks, healthcare workers, social care
workers, electricians, information technicians, cooks, logisticians, mechanical engineers,
painters, bricklayers, and carpenters. Individuals were selected for the analyses in this
paper only if they had not acquired diplomas in higher vocational or higher academic
education before 2014 and if they were not completing higher education in 2014. The
final sample consisted of 601 individuals.
3.2 Measures
Engagement in Further Formal Education
In 2014 and 2016, individuals were asked to denote all formal education programs they
had completed or in which they were actively engaged at the time of the survey. Par-
ticipants were asked to provide the name of the education alongside with the starting
and ending date, respectively, and whether they were still engaged in this education. In
higher vocational education examples include technical commercial employees, foreman
in the construction business, marketing experts, or food technologists. In higher aca-
demic education examples are, a bachelor’s degree in business administration or training
for a curative teacher and social workers. This information was coded according to
the educational level as apprenticeship, baccalaureate, higher vocational education, or
higher academic education.
Based on this information, a variable with three levels was constructed: 1 ‘no grad-
uation from higher education and not in higher education in 2016’, N = 356, 59%; 2
‘having graduated from higher vocational education after 2014 or being actively engaged
in higher vocational education’, N = 126, 21%; and 3 ‘having graduated from higher vo-
cational education after 2014 or being actively engaged in higher academic education’,
N = 119, 20%.
Workplace Factors
Task immanent learning opportunities and social support were taken from a Short Ques-
tionnaire for Job Analysis (Pru¨mper, Hartmannsgruber, & Frese, 1995). This question-
naire is based on the job diagnostic survey (Hackman & Oldham, 1975), an instrument
Higher Education in Switzerland 271
to assess social support (Frese & Zapf, 1987) and an instrument for stress-related work
analyses (Semmer, 1984). These sub-scales are relevant for learning at work (Kammer-
mann, Stalder, & Ha¨ttich, 2011; Keller, Meier, Gross, & Semmer, 2015; Na¨gele, 2013;
Stalder & Carigiet Reinhard, 2014).
Learning opportunities at work were assessed with three items (Pru¨mper et al., 1995),
for example, ‘I can learn a lot of new things at work’ based on the skill variety at work.
The response scale ranged from 1 ‘not at all’ to 5 ‘completely’, Cronbach’s alpha = .77,
mean = 3.8; standard deviation = .83, N = 601, min = 1, max = 5, and median = 4.
Social support was assessed with three items (Pru¨mper et al., 1995), for example, ‘I
can count on my colleagues when it gets difficult at work’. The response scale ranged
from 1 ‘not at all’ to 5 ‘completely’, Cronbach’s alpha = .77, mean = 4.1, standard
deviation = .76, N = 597, min = 1, max = 5, and median = 4.
Sociodemographic Factors
0pt The socioeconomic status of the parents was used as a proxy for the social origin.
The family’s international socioeconomic index was calculated as the highest value of
the fathers’ and mothers’ socioeconomic statuses. This information was based on the
parents’ occupations, coded according to the classification scheme of the Federal Institute
of Statistics. Mean = 51.7; standard deviation = 20.9; N = 601, min = 14.2, max =
88.7, median = 56.
The individuals were asked to name their citizenship according to their passport or
identity card. Individuals holding a Swiss and individuals holding a Swiss and any other
national passport or identity card were categorised as Swiss citizens. Non-Swiss citizens
were those without a Swiss passport or identity card. N = 601, Swiss citizenship N =
550, 91%, non-Swiss citizenship N = 51, 9%.
Gender was assessed with two categories, female and male. N = 601, female N = 371,
62%, male N = 230, 38%.
Value of Higher Education
The value given to further formal education was measured according to Wigfield et al.
(2017) with three items. ‘I consider further education and training for me as. . . a) use-
ful, b) important, c) attractive’. The response scale ranged from 1 ‘not at all true’ to 6
‘completely true’, Cronbach’s alpha = .84. Mean = 5.1, standard deviation = .83, N =
600, min = 1, max = 6, and median = 5.
Cohort/Age
The cohort was included in the analyses, as individuals within the two cohorts repre-
sented two different career situations. Cohort one had finished initial vocational educa-
tion and training between 2012 and 2014, whereas individuals from cohort two had been
working for several years on their jobs. The cohort corresponded with the age of the
individual, as the participants were younger in cohort one than in cohort two. Cohort
one N = 350, 57%, age (in 2014) = 21.84 years, standard deviation = 1.,7 Cohort two
N = 251, 43%, age (in 2014) = 27.7 years, standard deviation 2.5, t(646) = -21.95,
p < .01.
272 Na¨gele, Neuenschwander, Rodcharoen
4 Results
4.1 Expectations and Realisation of Educational Aspirations
To describe the sample according to their educational expectations, we first report the
results from cross-tabulating educational expectations in 2014 and their realisation in
2016. The expectation of achieving a particular formal educational type was assessed
in 2014 with a single item: ‘What is the highest degree you are going to attain in
your educational career?’. The response options were tracheotomised: 1 ‘No further
formal education, I am fine with a diploma in initial vocational education and training
with or without a baccalaureate (graduation on the upper secondary level)’, 2 ‘Federal
diploma in higher vocational education’, and 3 ‘Diploma in higher academic education’.
Table 1 reveals that only 35% of the individuals who expected in 2014 to achieve higher
vocational education were two years later engaged in higher vocational education. For
individuals who expected in 2014 to obtain higher academic education, the rate was
higher, and it differed between the two cohorts. The rate was 45% for the younger
cohort and 70% for the older cohort. The picture was different for those who told us in
2014 that they were planning to stay working, without further formal education at the
tertiary level. In 94% of the cases, these individuals were two years later still working and
not in higher education. The result also indicated that only a few individuals switched
between higher vocational education and higher academic education. In addition, if
individuals switched, they switched from higher academic education in 2014 to higher
vocational education two years later as can be seen in cohort one featuring the younger
individuals.
Overall, these descriptive results indicated that many individuals who told us in 2014
that they expected to attain diplomas in higher vocational education were not engaged
in higher vocational education two years later. This was different for individuals who
told us that they expected to be in higher academic education. A larger percentage of
these individuals were in higher academic education, especially in the older population
(cohort two).
Higher Education in Switzerland 273
Table 1: Educational expectations in 2014 and engagement in higher education in 2016
Higher
vocational
education
Higher
academic
education
No
higher
education
Higher
vocational
education
Cohorts 1&2* N
%
93
35%
9
3%
165
62%
266
100%
Higher
academic
education
Cohort 1** N
expected N
%
adj. residual
16
11.9
17%
1.8
44
55.2
46%
-3.3
36
28.9
37%
2.3
96
96
100%
Cohort 2 N
expected N
%
adj. residual
7
11.1
8%
-1.8
63
51.8
70%
3.8
20
27.1
212
-2.8
90
90
100%
Cohort 1&2 N
%
23
12%
107
58%
56
30%
186
100%
No higher
education
Cohort 1&2*** N
%
7
5%
1
1%
124
94%
132
100%
Legend. * χ2 (2) = 2.44, p = .30; ** χ2 (2) = 11.29, p=<01; *** χ2 (2) =1.47, p = .48; Separate
frequencies and residuals for the cohorts are presented only if the χ2 is statistically significant.
Overall: N = 601, cases with missing data N = 17.
4.2 Results Predicting Participation in Higher Education
To test the hypotheses, we calculated three multinomial regression models: model 1
with only the sociodemographic variables, model 2 with the value variable added, and
model 3 with the workplace variables added. The analyses were run using SPSS 25 (IBM
Corp., 2017). The results are summarised in Table 2. Due to the number of predictor
variables in the model, some cells have zero frequencies, which implies that the standard
errors need to be checked for unusually high values (Field, 2013). The results in Table 1
indicate that no conspicuous standard errors exist. It is notable that sociodemographic
variables alone could not explain engagement in higher vocational education (model 1).
Gender, which was a significant predictor of higher vocational education in model 1,
had no effect after we controlled for learning opportunities and social support (model
3). The results revealed two distinct sets of predictor variables for higher vocational
education and higher academic education. Learning at the workplace and (marginally
significant) team support predicted engagement in higher vocational education, whereas
social origin and nationality predicted engagement in higher academic education. The
value attributed to further higher education was predictive for both higher vocational
education and higher academic education.
274 Na¨gele, Neuenschwander, Rodcharoen
The hypotheses are discussed in detail based on model 3, and the results are sum-
marised in Figure 1. Hypothesis 1 was partly confirmed, as a positive effect of learning
opportunities on engagement in higher vocational education was found, odds ratio =
1.71, p <.01, but this was not so for higher academic education, odds ratio = .80, p
= .14. Hypothesis 2 was not confirmed, as social support had no significant effect on
engagement in higher education, neither for higher vocational education, odds ratio =
.74, p = .06, nor for higher academic education, odds ratio = 1.02, p = .89. However,
the result for higher vocational education was only marginally non-significant, indicat-
ing that social support might hinder further higher vocational education. Hypothesis 3a
was confirmed, as higher socioeconomic status predicted engagement in higher academic
education, odds ratio of 1.02, p = .02, but not in higher vocational education, odds ratio
= 1.00, p = .89. Hypothesis 3b was partly confirmed, as a higher chance existed for
Swiss citizens to complete higher academic education, odds ratio of 4.51, p = .01, but no
effect was found for higher vocational education, odds ratio = 2.12, p = .08. Hypothesis
3c was not confirmed, as gender had no effect on being engaged in higher education,
neither in higher academic education, odds ratio of .66, p = .08, nor in higher vocational
education, odds ratio = .72, p = .15. Hypothesis 4 was confirmed, as the value had a
substantial effect on becoming engaged in higher academic education, odds ratio = 2.84,
p <.01, or in higher vocational education, odds ratio = 2.88, p <.01. The cohort was
used as a control variable with an effect on being engaged in higher academic education,
odds ratio = .38, p <.01, indicating that younger individuals from cohort one were less
likely to attend higher academic education within two years. It takes more time to start
with higher academic education, for example, because individuals need to acquire voca-
tional baccalaureates before gaining access to it. In addition, formal education programs
typically start once a year, in autumn, whereas higher education programs can often be
completed on a short-term basis.
Higher Education in Switzerland 275
F
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276 Na¨gele, Neuenschwander, Rodcharoen
T
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2:
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Higher Education in Switzerland 277
5 Discussion
In this paper, we examined the effects of workplace characteristics (social support, learn-
ing opportunities), of sociodemographic factors (social origin, nationality, gender), and of
the value assigned to higher education as predictors of engagement in higher education.
We found predictors of being engaged in higher education that differ between higher
vocational and higher academic education. Following an individual’s graduation from
initial vocational education and training, workplace factors predict engagement in higher
vocational education, and sociodemographic factors explain engagement in higher aca-
demic education. A significant predictor for both groups is a high value attributed to
higher education.
Within the two years during the course of the study, we found that many individuals
with the expectation of attaining higher vocational diplomas in 2014 were not engaged
in 2016 in higher vocational education (66 %), which was different for higher academic
education, where fewer individuals were not yet involved in higher academic education
(55% in the younger cohort, 28% in the older cohort). This signifies that many individ-
uals with the expectation of achieving higher education diplomas were not yet actively
engaged in higher education.
Individuals who see learning options at the workplace will more likely complete higher
vocational education rather than continue working. Positive social support seemed to
hinder higher vocational education, although this result needs to be interpreted cau-
tiously, as it is only marginally significant. Contrary to our expectation, the sociode-
mographic variables of social origin, nationality, and gender had no significant effect
on completing higher vocational education. Higher vocational education seems to be
less socially selective compared with higher academic education. The effect of learning
opportunities at work is of greater importance. This finding is in line with reports on
the positive effects of informal learning on an individual’s motivation to develop specific
job-related competences (Janssens et al., 2017). This finding points to the considerable
function of workplace learning as a way of motivating employees to develop their pro-
fessional competences, which is the responsibility of individuals and organisations. A
proactive individual can create learning opportunities, for example, through job crafting
(Wrzesniewski & Dutton, 2001). It seems to be worthwhile for organisations to reflect
on how to support learning in the workplace and to discuss and implement supportive
learning cultures. Organisations with learning cultures can create, acquire, and trans-
fer knowledge and can reflect this knowledge and change its behaviour (Garvin, 1993),
as this positively affects commitment and intrinsic motivation (Joo & Lim, 2009). To
promote engagement in higher vocational education, it seems necessary to design a work-
place that is favourable for learning. Only if individuals experience that learning at work
is possible will they invest in further learning in higher vocational education, as they
can expect the transfer of the new knowledge and skills to the workplace to be possible.
The picture for individuals engaged in higher academic education was somewhat dif-
ferent, partly as expected. The sociodemographic variables of socioeconomic status and
nationality were as expected the best predictors, besides the value of further education.
However, the workplace factors were of no importance.
278 Na¨gele, Neuenschwander, Rodcharoen
6 Limitations
Although the study achieved its aim and the hypotheses could be tested, some limitations
should be pointed out. It would be interesting and necessary to replicate these findings
for specific trades. Despite the large sample size, these analyses would result in even
more cells with zero frequencies. Replications should be done with a focus on specific
trades to reduce the variance in the sample selected. Workplace factors were measured
as self-reports in this study. To achieve a more in-depth understanding, we suggest that
a more detailed measurement of workplace learning, social support, and satisfaction,
moreover from different perspectives and as repeated measures over a more extended
period, could provide valuable insights into how workplace factors shape motivation for
engagement in higher education.
7 Conclusion
The examination of the realisation of plans for higher education over time and relating
individual and workplace factors have pointed out considerable differences between indi-
viduals in higher vocational education and higher academic education. Individuals are
engaged in higher academic education due to their social origins and nationalities. This
finding adds to the existing knowledge that native people from families with better ac-
cess to education have a higher likelihood of attending higher academic education. These
processes of social exclusion and social selection processes seem to be very persistent.
On the other hand, we see that higher vocational education seems to offer socially non-
discriminating access to higher vocational education, even if higher vocational education
is financed primarily privately by the participants and the employers. Higher vocational
education is positioned as a provider of highly skilled workers for the labour market. We
find that the chance to become involved in higher vocational education increases if indi-
viduals have learning opportunities in the workplace and if their colleagues do not hinder
them if their social integration is too tight. Instead, it is the work environment, namely
the perception of learning opportunities and social support, that promote higher voca-
tional education. Individuals wanting to complete higher vocational education should
try to find or craft a workplace that allows them to learn. In addition, companies that
want their employees to move towards higher vocational education should support them
by designing workplaces as learning places. The unique contribution of this paper is to
compare these two distinct patterns of becoming engaged in higher vocational or higher
academic education.
From a theoretical point of view, we need to look at predictors of educational pathways
besides sociodemographic variables. We should integrate variables related to workplace
factors in our theories and empirical models.
From a policy perspective, this study described an example where higher vocational
education was designed as a parallel strand to higher academic education, which is
chosen by individuals with a distinct profile. It is noticeable that some people seem to
be motivated by the work environment to continue their education in higher education,
whereas others are motivated by heritage, which is linked to status.
Higher Education in Switzerland 279
Overall, we still need to find answers to deal with the finding that social origin and,
in our results especially, nationality are important factors that steer access to higher
academic education but not to higher vocational education. It might be worth looking
at selection and socialisation processes during vocational education and training more
closely to understand the discriminative processes that contribute to the discrimination
of individuals from a motivational perspective. Most importantly, a closer look at factors
that hinder individuals at work from becoming engaged in higher vocational education is
necessary. We have seen that many individuals who wish to complete higher vocational
education do not do this. These individuals start their higher education as a result
of an appropriate job design. Learning opportunities in the workplace trigger their
engagement, factors that can be shaped by both individuals and companies.
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284 Na¨gele, Neuenschwander, Rodcharoen
Biographical Notes
Dr Christof Na¨gele is a senior researcher at the Centre for Learning and Socialisation, In-
stitute for Research and Development, School of Education at the University of Applied
Sciences and Arts Northwestern Switzerland. His research interests focus on vocational
orientation, career choice of young people, learning and career development of adults
workers, individual, group level and structural resources in vocational education and
training.
Dr Markus P. Neuenschwander is a Professor at the Centre for Learning and Social-
ization, Institute for Research and Development, School of Teacher Education at the
University of Applied Sciences and Arts Northwestern Switzerland. His research focuses
on the school-to-work transition, socialisation in the family, school, and vocational edu-
cation and training.
M Sc Patsawee Rodcharoen is a junior researcher at Centre for Learning and Social-
isation, Institute for Research and Development, School of Education at the University
of Applied Sciences and Arts Northwestern Switzerland. Her interests focus on develop-
mental and social aspects of vocational education and training, vocational integration,
learning, and at-risk trajectories.
Acknowledgement
The State Secretariat for Education, Research, and Innovation (SERI) supported this
study (contract number 13100028). The interpretations, conclusions, and recommenda-
tions are those of the authors and do not necessarily represent the views of the SERI.