Topic

In Switzerland, two thirds of young people start initial vocational education and training (IVET) at upper secondary education which is primarily organised on a dual basis. This quote is high compared to other countries (OECD 2015). Nevertheless, as in the rest of the world, a certain trend towards academisation of the chosen educational pathways (Harwood 2010) can also be observed in Switzerland. In the last three decades the proportion of young people entering IVET has decreased from 77% to 68%, while the proportion entering general education (GE) has risen from 23% to slightly over 30% (FSO, own calculation).

In Swiss education policy, therefore, the fear is repeatedly expressed that the increasing educational aspirations of families, who are striving for a socially higher valued GE for their children, meets too much educational provision in GE. This would divert the better-performing school students away from IVET, leaving companies with only lower-performing young people as a recruitment base. This could lead to companies, offering demanding apprenticeships (e.g. technical apprenticeships), withdrawing from training (SCRE 2010, 2014). However, it can be assumed that this competition between IVET and GE for young people with a high school performance varies greatly between the 26 cantons: The proportion of IVET in the first year of training on upper secondary education ranges from 46% to 84% (FSO, own calculation).

Research has so far addressed the question of individual characteristics of students that influence the probability of entering IVET (for an overview, see Kriesi&Leemann 2020). The key factors that play a role in determining whether someone starts a IVET or GE programme are academic performance, the level of performance attended at lower secondary education (lower or higher performance level), social origin, gender, and place of residence. Male adolescents with medium to low academic performance, who attend the lower performance level at lower secondary, whose parents have achieved a lower educational status and who live in rural regions of German-speaking Switzerland are more likely to enrol in IVET.

Research Questions

Two questions have been neglected so far, which are examined in this paper:

(RQ1) How can the cantonal variation in the share of IVET be explained? What role do cultural and economic factors play while controlling for individual factors?

(RQ2) How does the educational structure on lower and on upper secondary level influence the probability of entering IVET: a/ cantonal performance structure at lower secondary level?; b/ cantonal proportion of general education at upper secondary level?

Theoretical Framework

Institutional, cultural, and economic factors are responsible for this great variance. The federalism of education in Switzerland means that the cantons decide independently on the provision and access regulations of GE. This has historically led to an uneven development in the structure of lower and upper secondary education (Gonon et al. 2016).

Culturally divergent educational cultures prevail between German- and Latin-speaking Switzerland, whereby IVET is valued more highly in the former (Geser 2003; Cattaneo&Wolter 2016). The cantons also differ according to the prevailing political ideologies (Rosenmund 2011), with right-wing conservative positions being more positive towards IVET than positions on the left-wing progressive political spectrum (Cattaneo&Wolter 2016). Finally, the cantons are characterised by different economic structures which have a bearing on both the supply of apprenticeships and the labour market's demand for qualifications (Glauser&Becker 2016). In cantons where the secondary sector predominates, IVET is stronger institutionalised.

Furthermore, it can be assumed that a high proportion of students in the higher performance level on lower secondary increases the probability of entering IVET due to limited places in GE, while a high proportion of general education decreases this probability.

Data: We analyse new and unique longitudinal register data for Switzerland which allows for reconstructing detailed educational pathways from lower secondary to upper secondary education. Since 2012, the Swiss Federal Statistical Office has applied a personal identifier in all its surveys in the education sector. This enables nationally harmonised and structured longitudinal data suitable for analysing educational transitions for the cohort which has finished lower secondary education in 2012 in the entire country (N= 82’955). We follow-up this cohort for two consecutive years – which allows to include students who have attended a bridging course before entering qualifying programms – and measure if pupils have enrolled in IVET until 2014 (dummy outcome variable). Analytical strategy: For answering our RQ we conduct multilevel binary logistic modelling (MLA) to analyse how institutional, cultural, and economic factors as well as educational structure of the 26 cantons (level 2) influence the probability of entering IVET while controlling for individual factors of students (level 1). As level 1 variables the educational performance level attended at lower secondary, the place of residence, gender and nationality of the pupils are included in the data. As level 2 variables, we use for RQ1 the canton's affiliation to the German- and Latin-speaking region, an indicator of traditionalism based on parliamentary elections (preservation of tradition, strong army, law and order, equal opportunities for foreigners), and the proportion of employees in the secondary sector (industry and commerce). For RQ2 we use for each canton the proportion of students in the higher performance level on lower secondary (a) and the proportion of students beginning GE in their first year of upper secondary education.

RQ1: The results show that in cantons where German is the main language, whose political culture is rather conservative and right-wing and whose economic structure is strongly characterised by the secondary sector, school leavers enter IVET more often, controlling for various individual factors. RQ2: The higher the proportion of students in the higher performace level on lower secondary education, the more students enter VET. The higher the proportion of general education in a canton, the lower the probability of entering VET. Conclusion: We can conclude that institutional, cultural, economic as well as the educational structure in the cantons strongly influence the probability of enrolment in IVET and are responsible for the great variance in the quote of IVET between the cantons. In a next step, we plan to analyse the question of whether there are interactions between the attended performance level at lower secondary education and the cantonal educational structure (crosslevel interactions of individual level 1 and cantonal level 2).

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