Session Information
09 SES 02 A, Findings from PISA: Student Attitudes, Perceptions and Aspirations (Part 2)
Paper Session
Contribution
The employment of human resources in science and technology occupations has grown faster than employment overall, often by a wide margin (OECD, 2008b). Many countries are now worried because not enough young people are interested in learning science subjects in school or through studying natural science or technology at the post-high-school level (OECD, 2008a). Researchers traditionally cite personality traits or individual interests as the most determinant factors for occupational choices (Holland, 1997; Lent, Brown, & Hackett, 1994; Phillips, 1997; Super, 1992). That’s why low interest in science is pointed out as a cause of the growing shortage of skilled young workers in scientific careers. The connection between school experience and vocational choices is a rare subject of discussion, even if motivational theories indicate the importance of learning and teaching for development of individual characteristics, like interest (e.g. Rocard et al., 2007). By contrast, we consider teaching and learning in school as explicitly relevant for occupational choices. This can play a substantial role especially in the case of science-related careers, because students learn science mainly in schools. Learning and teaching in science courses early in high school highly influences science related career choice relevant individual characteristics like interests and competency beliefs. Moreover, the schools may place different emphasis on teaching science. Some schools offer activities outside school hours to promote learning in science, which can have an impact on adolescents' considerations to pursue a scientific career.
The occupational preferences of adolescents are outlined by The Programme for International Student Assessment (PISA) in 2006 (OECD, 2007). The PISA-Database allows an analysis of students' career preferences in context of different characteristics related to science. We discuss how career preferences of adolescents can be modeled in context of individual and school characteristics. Thereby, the individual characteristics build the base-line for the adolescents’ choices to take up a scientific career. The individual characteristics like interests are influenced by schools, but the schools can also directly influence the students' motivation to take up a scientific career. The discussion of these interactions is used to generate an integrated model on two levels (student and school characteristics) to explain students' motivation to take up a scientific career. In the first step, the theoretical model is verified by German adolescents in the ninth grade. The theoretical model represented cannot be seen as blanket because of its reference to PISA-Data. It’s rather a question of whether the characteristics of learning and teaching in school can be seen as relevant for adolescents’ choices to take up a career in natural science later on or not. Therefore, the main purpose of our contribution is to raise discussion about the meaning of learning and teaching in school in the context of career choices in general and in the context of careers in natural science in particular.
Method
Expected Outcomes
References
Eccles, J. S. (1983). Expectancies, Values, and Academic Behaviors. In J. T. Spence (Ed.), Achievement and Achievement Motives. Psychological and Sociological Approaches (pp. 75-146). San Francisco: W. H. Freeman and Company. Holland, J. L. (1997). Making Vocational Choices. A Theory of Vocational Personalities and Work Environments (Vol. 3). Florida: Psychological Assessment Resources. Lent, R. W., Brown, S. D., & Hackett, G. (1994). Toward a Unifying Social Cognitive Theory of Career and Academic Interest, Choice, and Performance. Journal of Vocational Behavior, 45(1), 79-122. Phillips, S. (1997). Toward an expanded definition of adaptive decision making. The career development quarterly, 45, 275-287. OECD. (2007). PISA 2006: Science competencies for tomorrow´s world. Paris: OECD. OECD. (2008a). Encouraging Student Interest in Science and Technology Studies. Paris: OECD. OECD. (2008b). OECD Science, Technology and Industry Outlook 2008. Paris: OECD. Rocard, M., Csermely, P., Jorde, D., Lenzen, D., Walberg-Henriksson, H., & Hemmo, V. (Eds.). (2007). Science education now: A renewed pedagogy for the future of Europe. Brussels: European Commission. Super, D. E. (1992). Toward a comprehensive theory of career development. In C. J. Shinkman (Ed.), Career development: theory and practice (pp. 35-64). Springfield, Illinois: Charles C. Thomas.
Search the ECER Programme
- Search for keywords and phrases in "Text Search"
- Restrict in which part of the abstracts to search in "Where to search"
- Search for authors and in the respective field.
- For planning your conference attendance you may want to use the conference app, which will be issued some weeks before the conference
- If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.