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A tree with many branches: How the TREE study is growing

The Swiss TREE study “Transitions from Education to Employment”—one of the models of the National Education Panel Study (NEPS)—has been in existence for almost 20 years now. As part of LIfBi Lectures, the two project heads Prof. Dr. Ben Jann and Dr. Thomas Meyer from the Institute of Sociology at the University of Bern reported on panel progress and some results.

The TREE study analyzes the transition of young people from school to adult life. The first sample (TREE1) emerged from the PISA study in 2000 and started with over 6,000 young people aged 16 on average. It has since been followed by ten waves of surveys, in which the educational and labor market histories of the panel participants were investigated in detail.

In 2016, a second sample (TREE2) was drawn in the same way as TREE1, in which almost 10,000 young people (initial sample) have since been surveyed longitudinally. According to Meyer, it is thus comparable in terms of age with NEPS Starting Cohort 3 “Grade 5“ (SC3). Like the NEPS data, the TREE data are also made available to the scientific community free of charge—that is, they are published online by the Swiss Centre of Expertise in the Social Sciences (FORS) in Lausanne. The first data of the second cohort (TREE2) will be made available from October 2020 and will comprise the initial survey and the first two follow-up waves.

The design of TREE2 as a baseline survey

Co-head of the project Thomas Meyer gave an insight into the research design and the survey instruments used, which—similar to the NEPS—record not only sociodemographic data but also competencies, personality, health, values, and aspirations, to name but a few. Since 2010, the family situation, for example, data on childcare, has also been collected.

"We designed TREE2 as a baseline survey to which—like a Lego brick—other qualitative or experimental studies, subsamples or register data can be added," described Thomas Meyer the design of the study. The TREE data are among the five most frequently used social science data sets in Switzerland. Meyer emphasized the high value of active data marketing, for example, at data fairs and exhibitions.

The long shadow of early tracking

In the second part, Meyer presented characteristics of the Swiss education system, which is marked by a pronounced institutional heterogeneity (school system of 26 cantons, four languages) as well as early and strict segregation ("tracking"). This results in a whole web of different educational trajectories. "These diverse trajectories are also expressed in the title of the TREE study, as they unfold like the branches of a tree," Meyer described the comprehensive, multidimensional view of educational trajectories.

Meyer critically examined the fact that although the Swiss education system sees itself as fair and permeable, tracking has shown that students' trajectories are clearly predetermined from an early age. Ultimately, this leads to injustices and strong, stereotypical gender effects at all levels of education.

Gender gap in STEM professions

In the last part of the LIfBi Lecture, Ben Jann presented the first analyses of the TREE2 cohort, whose data have not yet been published. He explored the question of why women in Switzerland are found quite rarely in STEM occupations—that is, in science, technology, engineering, and mathematics.

The result of the TREE2 analysis was that while differences in competencies do explain some of the differences between women and men in their STEM aspirations, self-assessment of these competencies plays a much more significant role: Women are less likely to choose STEM professions because they underestimate their competencies compared to men. "The difference in self-assessment that we can observe for Switzerland explains a large part of the gender gap," Jann summarizes the analyses.

LIfBi research on STEM students

The findings of Dr. Ilka Wolter, Head of Department "Competencies, Personality, Learning Environments" at LIfBi, Lisa Ehrtmann (also LIfBi), Prof. Dr. Tina Seidel (TU Munich) and Prof. Dr. Barbara Drechsel (University of Bamberg), who used NEPS data to investigate the professional goal orientation of women and men in STEM programs, fit in well with these findings. As a result of a study in 2019, they concluded that students differ in their career goals during their studies depending on the courses of study in which they enroll. Gender-stereotypical distributions occur in STEM and non-STEM majors: Men are still more likely to choose a program with a STEM career goal, while women are clearly in the majority in the humanities and social sciences. STEM students tend to pursue economic goals for their professional future, while non-STEM students tend to strive for public welfare or social goals. But: Regardless of whether women study STEM subjects or not, their professional goals tend to remain oriented towards the common good or social goals.

Website of TREE study at the University of Bern

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