The growing demand for STEM (Science, Technology, Engineering, and Mathematics) professionals to address global challenges—such as climate change, sustainable mobility, and energy transition—has led to increased attention on STEM education pathways, including Vocational Education and Training (VET) (Pokropek, 2024). Despite efforts to promote STEM education through policy initiatives, workforce shortages persist across the EU (OECD, 2014). One key obstacle is limited access to STEM education at the early, pre-vocational stages. Students who have fewer opportunities to engage with STEM subjects in lower-secondary education are less likely to pursue STEM-focused paths later on. This study investigates how the availability of STEM education in Dutch pre-vocational lower-secondary schools influences students' decisions to pursue a STEM profile, enroll in STEM courses, and continue in STEM-oriented upper-secondary VET programs. The central research question is: How does the availability of STEM education in pre-vocational schools impact students' likelihood of pursuing STEM pathways in lower secondary and upper secondary vocational education? By providing empirical insights, this research contributes to ongoing discussions about policies that can encourage more students to pursue careers in STEM fields.

This research employs an instrumental variable (IV) approach to address the potential endogeneity between STEM education supply and student choices. The instrument used is the distance between students’ home addresses (measured in their final year of primary education) and the nearest pre-vocational lower secondary school offering STEM education. By exploiting variation in proximity, we estimate the causal effect of STEM education availability on students’ probability of choosing a STEM profile in pre-vocational education, enrolling in at least one STEM course, and selecting a STEM program in upper-secondary VET. Data for this study comes from administrative educational records from the Netherlands, which provide information on students’ residential addresses, school characteristics, and educational choices. Regression analyses are used to estimate the effect of school proximity on STEM selection, controlling for socio-demographic and school-level factors. The IV strategy ensures that our estimates capture the exogenous variation in educational supply rather than unobserved student characteristics.

We expect that proximity to schools offering STEM education will positively influence the likelihood of students selecting STEM profiles, enrolling in STEM courses, and pursuing STEM programmes in upper-secondary VET. The research aims to demonstrate the potential barriers posed by limited access to STEM offerings at the pre-vocational stage, and how this affects students’ longer-term academic and career decisions in STEM fields.

OECD (2024), Bridging Talent Shortages in Tech: Skills-first Hiring, Micro-credentials and Inclusive Outreach, Getting Skills Right, OECD Publishing, Paris, https://doi.org/10.1787/f35da44f-en. Pokropek, A. (2024), STEM Competencies, Challenges, and Measurements: A Literature Review, in Mazzeo Ortolani, G., Karpinski, Z., and Biagi, F. (eds.), Publications Office of the European Union, Luxembourg, doi:10.2760/9390011, JRC138618.