02 SES 03 B, Less Successful VET Students
Training success is a central requirement for career development. However, dropouts in VET are an important and current topic in several countries in Europe (Cedefop, 2016). Previous research shows diverse reasons to explain premature contract terminations (PCT) by individual, institutional as well as vocational explanatory variables (e.g. Rohrbach-Schmidt & Uhly, 2015; 2016). In career research job persistence is typically linked to person-environment (P-E) fit (e.g., Kristof-Brown et al., 2005). Kristof-Brown et al. (2005) defined P-E fit “as the compatibility between an individual and a work environment that occurs when their characteristics are well matched.” This compatibility relates to different levels, like vocation, job, work group and supervisor (e.g., Kristof-Brown et al., 2005). Regarding the transition from school to VET, we assume that the compatibility of personal and vocational characteristics is a meaningful pre-condition for coping with training requirements. This compatibility type is called person-vocation (P-V) fit, which is a subdimension of P-E fit.
However, analyses focusing on consequences of P-V fit in VET are rare. Pioneer research on person-vocation (P-V) fit in VET is published by Nägele and Neuenschwander (e.g. 2015; 2016) as well as Volodina et al. (2015). Nägele and Neuenschwander (e.g. 2015; 2016) show that training satisfaction as well as the intention to complete the training program are positively affected by a perceived person-vocation fit. Volodina et al. (2015) show the importance of Realistic interests in technical training programs. However, in comparison to research about career development (e.g. Kristof-Brown et al., 2005) several research gaps exist in the context of VET. For example, there is no critical discussion of suitable indicators and measurement methods for P-V fit. Moreover, consequences of P-V fit should be considered in a long-term manner, e.g., the realization of a PCT. Furthermore, research should refer to samples with heterogeneous vocational environments. In our paper presentation we will address these three research gaps and analyse the influence of selected P-V fit indicators on training satisfaction and PCT.
P-V fit has to be seen as a multidimensional construct, because occupations differ by diverse demands. Therefore, we regard the following three indicators as relevant to predict perceived training satisfaction as well as PCT.
(1.) Educational match: This refers “to a situation in which the level of education attained by an individual does (not) correspond to the educational requirements of her job” (Mateos-Romero & Salinas-Jiménez, 2018).
(2.) Vocational interest congruence: People prefer a working environment that matches their interests. Conceptionally, vocational interest congruence is based on assumptions of Hollands’ RIASEC model (Holland, 1997). Six dimensions of vocational interests are distinguished: (R) Realistic, (I) Investigative, (A) Artistic, (S) Social, (E) Enterprising and (C) Conventional. Several studies show that interest congruence can improve job satisfaction as well as persistence at work (Hoff et al., 2020; van Iddekinge et al., 2011).
(3.) Vocational skill congruence: General skills are necessary for completion a vocational training program (Winther & Achtenhagen, 2009).
For the analysis, the starting cohort 4 (version 10.0.0) of the National Education Panel (NEPS: Blossfeld et al., 2011) is used. This dataset contains longitudinal information of 16,425 German adolescents throughout their life course since their first measurement in the 9th grade in autumn 2010. The dataset is reduced to trainees who started a company-based training program in Germany’s dual VET system. Due to the fact that NEPS survey is ongoing, only trainees with a training contract termination during first 12 month of training or whose training episode is longer than 12 months are considered for the analyses (n = 4.097; 151 ISCO 08 groups). As dependent variables we use training satisfaction (mean = 7.880, SD = 1.690 on a 11-point Likert scale) and PCT. Training satisfaction is analysed by tobit regressions, because the data is right-censored. Binomial logistic regressions are used to analyse PCT in first training year. Different individual variables of the NEPS participants are used as independent variables: no or low school-leaving qualification, intermediate school-leaving qualification, high school-leaving qualification, vocational interests before starting the training program (Realistic, Investigative, Artistic, Social, Enterprising and Conventional) as well as skills (mathematics, science and reading). To determine P-V fit, the dataset is matched with information on the share of low qualified adolescents in the respective occupation and O*Net expert ratings of interests and skills. For an easier interpretation in regression models, scales of vocational interests and skills as well as all variables to describe vocational environment are z-standardized (mean = 0, standard deviation = 1). To investigate P-V fit indicators on dependent variables, interactions terms with polynomial regression coefficients are built as it is recommended in P-E fit research. Undereducation is determined by an interaction term between the variable no or low school-leaving qualification and the variable share of beginning trainees with at least intermediate qualifications in trainees’ occupations. Overeducation is investigated using two interaction terms: (1) intermediate school-leaving qualification and (2) high school-leaving qualification and share of low-qualified beginning trainees in trainees’ occupations. For vocational interest and skill congruence interaction terms for each dimension between individual value in NEPS dataset and value for the occupation are used. In each regression model, we control for gender, migration background, GPA, information about discontinuous educational pathways, parental education as well as regional hiring challenges.
Our results confirm and complement previous findings in VET research to the influence of P-V fit on training satisfaction and PCT. First, we find that training satisfaction of intermediately qualified trainees increases with the share of trainees with low qualifications in the occupation (moderate overeducation). Second, under- and overeducation do not influence PCT. Additionally, vocational interest congruence can reduce the probability of PCT in the dimension of Realistic interests. This finding generalises previous findings toward the importance of Realistic interest congruence (Volodina et al., 2015) due to considering a more comprehensive and representative occupational structure of VET in our sample. Finally, our results reveal, that skill congruence affects neither training satisfaction nor the probability of PCT. Overall, the results show that P-V incompatibility is not a major problem for VET in Germany. Reasons could lie in career and work adjustment processes during the training process. However, evidence with respect to specific mechanisms in the training process is a research desideratum and should be considered in further research and will be discussed at the conference. However, our results also hint towards the importance of trainees’ characteristics for training satisfaction as well as PCT regardless of the characteristics of the vocational environment. For instance, mathematical competence provides a preventive effect on PCT. Also, negative effects are observable. Enterprising and Artistic interests as well as reading competence increase the probability of PCT, and scientific literacy leads to lower training satisfaction. It can be assumed that high levels in these dimensions cannot be applied in occupations within the vocational structure of the German dual system. Thus, these findings could indicate a general need-supply incompatibility in Germanys’ VET system. However, further research is necessary to investigate such effects in VET.
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