This paper aims to explain the interests in STEM (Science, Technology, Engineering and Mathematics) careers among primary school children in Croatia. The problem of declining interest of youth in this area is relatively new, emerging and socially very relevant, resulting in shortage of STEM graduates and experts (EU, 2004; Osborne & Dillan, 2008; UNESCO, 2010). In this study we used Holland's model of vocational interests and work environments (Holland, 1959, 1997) to explore STEM interests and to see how and where they fit into Holland's interest themes. Holland’s theory is based on Person–Environment fit paradigm which assumes that interests directly influence educational and career choices and that people are inclined toward academic or work environments that are congruent with their interests. The congruence between an individual’s interests and work environment leads to greater satisfaction and career stability. Holland (1959, 1997) proposed six categories for classifying individuals and work environments: Realistic, Investigative, Artistic, Social, Enterprising, and Conventional, also referred to as the RIASEC model. The RIASEC interest types and work environments are organized in a circular hexagonal model that implies an equal distance between the types. Interests and work environments which are adjacent (e.g. RI) are more similar than the alternate ones (e.g. RA), while alternate types are more similar than opposite interests types (e.g. RS). Prediger (1982) proposed two bipolar dimensions that underlie the RIASEC model: the People-Things dimension that distinguishes between Social and Realistic types, and the orthogonal Data-Ideas dimension that differentiates Conventional and Enterprising types from Investigative and Artistic. The hexagonal structure of interest types was cross-culturally confirmed (Rounds & Tracey, 1996).

With reference to previous research, the major difference in interests toward STEM careers can be found along the People-Things dimension. It has been found that People-Things orientations are good predictors of a choice of STEM college majors (Woodcock et al., 2013). Lubinski & Benbow (2006) argued that difference in People-Things interest dimension contributes to the poor representation of women in STEM occupations, while Su, Rounds, & Armstrong (2009) and Lippa (1998) demonstrated that sex differences in interests are the largest along the People-Things dimension. Things work activities involve tasks that do not include other people but involve working with tools or machines, while People work tasks involve other persons, and activities like caring for others or teaching. Many disciplines in natural sciences, such as physical science, astronomy, and chemistry involve heavy Realistic interests placed on the Things pole within the hexagon (Su & Rounds, 2015). Thus, it is expected that majority of STEM occupations are saturated with Realistic features of working environment. On the other hand, Investigative type of interest captures interests in science and research, and could also be an indicator for the interests in STEM careers.

It is expected that most of STEM occupations have strong Realistic and Investigative component, and to lie close to the Things pole, but STEM is a broad term with heterogeneous sub-disciplines. According to the list of STEM occupations in O*NET database there are clusters of STEM occupations that have another dominant RIASEC code. There are STEM occupations with strong Artistic (e.g. Landscape Architects –AIR), Social (e.g. Chemistry Teachers, Postsecondary – SIR), Enterprising (e.g. Engineering Managers–ERI), and Conventional components (Financial Analysts– CIE). Therefore, the aim of this research is to find out how primary school children structure their interest toward STEM occupations, to which extent they differentiate between the STEM fields, and where their interests toward those fields can be placed within the general RIASEC model of interests.

EU (2004). Europe needs more scientists! Brussels: European Commission, Directorate- General for Research, High Level Group on Human Resources for Science and Technology in Europe. Holland, J. L. (1959). A theory of vocational choice. Journal of Counseling Psychology, 6, 35-45. Holland, J. L. (1997). Making vocational choices: A theory of vocational personalities and work environments (3rd ed.). Odessa, FL: Psychological Assessment Resources, Inc. Jones, L. E., & Koehly, L. M. (1993). Multidimensional scaling. In G. Kern & C. Lewis (Eds.), A handbook for data analysis in the behavioural sciences: Methodological issues (pp. 95–163). Hillsdale, NJ: Erlbaum. Kier, M. W., Blanchard, M. R., Osborne, J. W., & Albert, J. L. (2014). The development of the STEM career interest survey (STEM-CIS). Research in Science Education, 44(3), 461-481. Lippa, R. (1998). Gender-related individual differences and the structure of vocational interests: The importance of the people-things dimension. Journal of Personality and Social Psychology, 74, 996–1009. O*NET The Occupational Information Network, US Department of Labor/Employment and Training, https://www.onetonline.org Osborne, J., & Dillon, J. (2008). Science Education in Europe: Critical Reflections. London: The Nuffield Foundation. Prediger, D. J. (1982). Dimensions underlying Holland’s hexagon: Missing link between interests and occupations? Journal of Vocational Behavior, 21, 259-287. Rounds, J., & Tracey, T. J. (1996). Cross-cultural structural equivalence of RIASEC models and measures. Journal of Counseling Psychology, 43, 310-329. Su, R., & Rounds, J. (2015). All STEM fields are not created equal: People and things interests explain gender disparities across STEM fields. Invited contribution to S. J. Ceci, W. M. Williams, & S. Kahn (Eds.), Underrepresentation of women in science: International and cross-disciplinary evidence and argument on the debate, special issue in Frontiers in Psychology. Su, R., Rounds, J., Armstrong, P. I. (2009). Men and things, women and people: A meta-analysis of sex differences in interests. Psychological Bulletin, 135, 859-884. Tracey, T. J. G. (2002). Personal Globe Inventory: Measurement of the spherical model of interests and competence beliefs [Monograph]. Journal of Vocational Behavior, 60, 113–172. UNESCO. (2010). Engineering: Issues, Challenges and Opportunities for Development. Paris: UNESCO. Woodcock, A., Graziano, W. G., Branch, S. E., Habashi, M. M., Ngambeki, I. & Evangelou, D. (2012). Person and thing orientations: Psychological correlates and predictive utility. Social psychological and personality sciences. 3 (2), Online Version April 24, 2012.