23 SES 13 C, STEM Education
Meeting the demand for STEM workers – that is, for employees with a science, technical engineering or mathematics background – has been a high priority across the European Union (EU). There is widespread concern that the potential lack of sufficient STEM labour supply may hinder future economic development and reduce the economic competitiveness of the EU. This presentation looks at adolescents’ career plans and their correlates to better understand why men are more likely than women to study STEM subjects and enter the corresponding jobs.
Within different cultural contexts, educational and career decisions are anchored in the choices students and their families make in adolescence. Therefore, exploring factors that shape career expectations of very young students is paramount. To achieve a greater gender balance in STEM occupations, interventions should focus on (early) educational careers and the early divergence of female and male career expectations (Archer et al., 2010, 2013).
While variations in science and mathematics teaching across schools may contribute to within-country variations in STEM aspirations, researchers have started looking into cross-country differences, trying to understand how historical and cultural social differences, in particular in labour markets and education systems, may contribute to the variation in males’ and females’ aspirations to STEM careers. Social norms and values have repeatedly been found to influence students’ career decisions. Research has also explored general characteristics that differentiate entire education systems, and curriculum-specific characteristics concerning the differences in mathematics or science teaching. The attention was focused on the former, exploring the ways students in different types of educational systems develop an interest in STEM careers, and less consideration has been paid to subject-specific policies.
In this research, we are focusing on all three layers of cross-country differences: cultural differences, general characteristics of educational systems and the characteristics specific to school curricula. We explore cultural differences by analysing gender essentialist values, i.e. the widely shared conviction that women are naturally suited to occupations involving inter-human communication and caring activities, while men are naturally suited to occupations involving technology and abstract problem-solving, was argued to be the major factor enhancing gender-typical career choices (Sikora and Pokropek, 2012; Charles, 2017).
General characteristics of educational system are represented by three forms of relevant institutional arrangements: the level of tracking, vocational orientation and standardisation. It is argued and supported by evidence that educational systems that differ with respect to tracking, vocational orientation and degree of standardisation produce different outcomes for students in terms of education achievement, equality of opportunities and labour market placement (Bol and Van de Werfhorst, 2013). A number of studies have demonstrated that these institutional arrangements may affect students’ educational and occupational preferences (Buchmann and Dalton, 2002; Sikora & Pokropek, 2012a).
Curriculum-specific characteristics are addressed by analysing: (1) the existence of a national strategy to evoke interest in these subjects; (2) an explicit attempt to address the gender imbalance in STEM; (3) some elements of the content of science and mathematics curricula; and (4) the existence of ability grouping in the classroom.
To explore adolescent career expectations we use PISA 2015 data together with additionally collected country level indicators. Altogether, we examine 35 country-level indicators that, from a theoretical point of view, may be relevant for STEM career choices and for gender differences in those choices. From a statistical point of view, having 34 country-level indicators that could potentially explain the level and the gender gap in STEM expectations (in total, 2 × 34 parameters) makes it impossible to conduct analysis in a single statistical model. To overcome this problem we adopt a stepwise procedure that consists of two general steps: (1) initial screening and (2) backward stepwise selection of multilevel models. This results in a modelling strategy in which the initial inclusion of country-level predictors is based on prior research as well as the need to demonstrate the extent to which educational and STEM-promoting policies correlate with STEM-related youth career expectations. The second step isolates the relevant country characteristics based on substantive as well as statistical criteria, leading to the most efficient and informative model specification
Regarding the country-level factors, our findings reveal two important positive influences on students’ STEM career plans: the share of 15-year-old students in a vocational programme and the existence of a compulsory national examination in maths. First, we find that the share of 15-year-old students who are enrolled in a programme whose curriculum is pre-vocational or vocational is significantly positively related to the number of students with STEM career expectations. This is not so surprising, given the relative importance of STEM-related subject areas in vocational schooling at the upper secondary level. Assuming that these schools can either directly lead to (non-professional) STEM careers or prepare for entering a science-related higher education path, vocational programmes at the upper secondary level appear to positively influence students’ motivations for STEM careers. Our individual-level analysis shows a positive association between attending a vocational programme and developing an interest in a STEM career in Austria, Croatia, the Czech Republic, Slovakia and Slovenia. Our second finding from the country-level analysis suggests a significant positive association between compulsory national examination in maths and students’ plans to enter a STEM occupation. A possible mechanism behind the positive association we have identified is that facing a compulsory maths exam at the end of secondary education may force students to continue studying this subject, even if they might have dropped, or at least neglected, this area of study in a less standardised system.
Archer, L., DeWitt, J., Osborne, J., Dillon, J., Willis, B., & Wong, B. (2010). “Doing” science versus “being” a scientist: Examining 10/11-year-old schoolchildren’s constructions of science through the lens of identity. Science Education, 94(4), 617–639. Archer, L., DeWitt, J., Osborne, J., Dillon, J., Willis, B., & Wong, B. (2013). Not girly, not sexy, not glamorous’: Primary school girls’ and parents’ constructions of science aspirations. Pedagogy, Culture and Society, 21(1), 171–194. https://doi.org/10.1080/14681366.2012.748676 Bol, T., & Van de Werfhorst, H. G. (2013). The Measurement of Tracking, Vocational Orientation, and Standardization of Educational Systems: A Comparative Approach. Gini Discussion Paper 81. Retrieved from http://www.gini-research.org/system/uploads/532/original/81.pdf?1380554366 Buchmann, C., & Dalton, B. (2002). Interpersonal influences and educational aspirations in 12 countries: the importance of institutional context. Sociology of Education, 75(2), 99. https://doi.org/10.2307/3090287 Charles, M. (2017). Venus, Mars, and math: gender, societal affluence, and eighth graders’ aspirations for STEM. Socius, 3, 1–16. Sikora, J., & Pokropek, A. (2012a). Gender segregation of adolescent science career plans in 50 countries. Science Education, 96(2), 234–264.
00. Central Events (Keynotes, EERA-Panel, EERJ Round Table, Invited Sessions)
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