Session Information
11 SES 11 A, Quality Education to Secure Career Development
Paper Session
Contribution
The Lower Silesian Barometer of Plans and Aspirations is a large-scale regional research initiative aimed at monitoring and analyzing the educational and career aspirations of students completing key stages of formal education. The project aligns with the objectives of the Integrated Skills Strategy 2030—Poland’s national skills development strategy—and supports the regional coordination of vocational education, higher education, and lifelong learning (Ministry of National Education, 2019).
The study aims to determine the structure of educational and career plans among students completing primary and secondary education, analyze the factors influencing their decisions, and assess the alignment of their aspirations with labor market needs. Designed as a population study, the project includes all students completing a given stage of education in a given cohort, with an estimated sample size of approximately 50,000 students annually. The longitudinal structure enables annual measurements, allowing for quasi-panel analyses in the first three years and full panel studies starting in the third year, tracking the same student cohorts at critical educational and career transition points (Piwoński, 2019). The first wave of the study is scheduled for February 2025.
The analysis will be conducted at multiple levels, ranging from individual schools to municipalities, districts, and the regional level. Additionally, contextual data (e.g., gender, age, nationality, parental education and occupation, place of residence) will be collected, enabling in-depth studies on social mobility (both intergenerational and intragenerational), educational inequalities, and environmental determinants of student outcomes (Chetty et al., 2020; Sikora & Devlin, 2021; Herbst & Sobotka, 2014).
A key methodological component is the use of spatial mapping techniques, which will facilitate a comprehensive analysis of regional patterns in educational aspirations and their alignment with local labor market opportunities. These techniques will allow for trend identification and inequality assessment, providing policymakers, career counseling institutions, and educational administrators with valuable insights for shaping education policies (Reardon, 2019).
At ECER 2025, we will present the program’s framework and preliminary findings from the first wave of data collection. The discussion will focus on the potential of large-scale regional studies in supporting educational planning and data-driven policy development, ensuring that students’ aspirations align more effectively with the evolving demands of the labor `market.
Method
The Lower Silesian Barometer of Plans and Aspirations is based on a quantitative, population-based research approach in educational studies, allowing for comprehensive monitoring of youth educational and career aspirations. The primary research instrument is a structured questionnaire, covering key areas such as educational and career aspirations (preferred educational pathways, career interests, key factors influencing career choices, expectations regarding further education and employment); determinants of aspirations (family background, socioeconomic status, educational background of parents, aspirational models within the family, school environment, peer influence, and local community impact); and alignment with labor market needs (students’ employment expectations, perceived attractiveness of various economic sectors, willingness to migrate for educational and career opportunities). The questionnaire is conducted online, enabling efficient data collection across the entire region. The study is implemented in collaboration with schools and educational authorities, ensuring broad participation. To enhance the reliability and validity of the research tool, the questionnaire underwent a pilot test on a smaller group of students, leading to its refinement. The survey data will be supplemented by contextual sources, including economic reports and employment forecasts, allowing for an assessment of how well students’ educational aspirations align with current and projected labor market demands (Chłoń-Domińczak, 2015); administrative data, providing insights into academic performance, social mobility, and career trajectories of school graduates; and spatial data, analyzing regional conditions affecting educational and career aspirations in relation to local educational opportunities and labor market demands. An essential methodological component is the use of Geographic Information Systems (GIS), which enables spatial mapping and analysis of educational aspirations and their alignment with available career paths in the region (De Smith et al., 2018). Spatial analysis helps visualize regional disparities, identify areas with high and low alignment between aspirations and employment opportunities, and formulate strategies for adjusting educational offerings to meet labor market needs. The longitudinal research design allows for tracking changes over time rather than merely assessing a static snapshot of students’ aspirations. In the first three years, quasi-panel analyses will be conducted, comparing results among consecutive cohorts of students completing primary and secondary education. From the third year onward, full panel analyses will enable tracking individual student trajectories over several years (Piwoński, 2019).
Expected Outcomes
The first wave of the study (February 2025) will provide: 1. Identification of patterns in educational aspirations, differentiating between academic and vocational pathways; 2. Analysis of the socio-economic determinants of educational and career choices, including the role of family background; 3. Detection of gaps between student aspirations and labor market demands, helping address potential skill mismatches; 4. Assessment of regional disparities in educational choices, considering economic and infrastructural factors (OECD, 2018; Lareau, 2011; Alexander et al., 2014). Findings will be analyzed at the school, municipal, and district levels, enabling localized recommendations for policy and practice. The panel component (starting in the third year) will allow for tracking changes in aspirations over time, providing insights into the stability and evolution of students’ preferences. The long-term objective of the project is to enhance data-driven decision-making in education, improve career counseling, and increase the flexibility of the education system in response to labor market shifts.
References
1.Alexander, K. L., Entwisle, D. R., & Olson, L. S. (2014). The Long Shadow: Family Background, Disadvantaged Urban Youth, and the Transition to Adulthood. Russell Sage Foundation. 2.Chetty, R., Friedman, J. N., Hendren, N., Jones, M. R., & Porter, S. R. (2020). The Opportunity Atlas: Mapping the childhood roots of social mobility. Nature, 576(7789), 232–237. https://doi.org/10.1038/s41586-020-2563-2 3.Chłoń-Domińczak, A. (Red.). (2015). Regionalne uwarunkowania decyzji edukacyjnych – wybrane aspekty. Warszawa: Instytut Badań Edukacyjnych. 4.De Smith, M. J., Goodchild, M. F., & Longley, P. A. (2018). Geospatial Analysis: A Comprehensive Guide to Principles, Techniques and Software Tools (6th ed.). The Winchelsea Press. 5.Deci, Edward L.; Ryan, Richard M. Die Selbstbestimmungstheorie der Motivation und ihre Bedeutung für die Pädagogik Zeitschrift für Pädagogik 39 (1993) 2, S. 223-238 . https://doi.org/10.25656/01:11173 6.Herbst, M., & Sobotka, A. (2014). Mobilność społeczna i przestrzenna w kontekście wyborów edukacyjnych. Warszawa: Instytut Badań Edukacyjnych. 7.Lareau, A. (2011). Unequal Childhoods: Class, Race, and Family Life (2nd ed.). University of California Press. 8.Ministerstwo Edukacji Narodowej. (2019). Zintegrowana Strategia Umiejętności 2030. Warszawa: Ministerstwo Edukacji Narodowej. 9.OECD. (2018). Equity in Education: Breaking Down Barriers to Social Mobility. Paris: OECD Publishing. 10.Piwoński, Z. (2019). Badania panelowe w edukacji. Studia poprzeczne i prowadzone wzdłuż czasu – Próba systematyki i analizy. Toruń: Wydawnictwo Adam Marszałek. 11.Polska Agencja Rozwoju Przedsiębiorczości. (2020). Bilans Kapitału Ludzkiego 2016-2023 – Metodologia badania. Warszawa: PARP. Dostępne na: https://www.parp.gov.pl 12.Reardon, S. F. (2011). The widening academic achievement gap between the rich and the poor: New evidence and possible explanations. W: Murnane, R. J., & Duncan, G. J. (Eds.), Whither Opportunity? Rising inequality, schools, and children's life chances (s. 91–116). Russell Sage Foundation. 13.Sikora, J., & Devlin, M. (2021). Education and social mobility: Possibilities, reproductive structures and contexts. International Studies in Sociology of Education, 30(1-2), 1–10. https://doi.org/10.1080/09620214.2021.1995778
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