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10 - Predicting career aspirations and university majors from academic ability and self-concept

A longitudinal application of the internal–external frame of reference model

Published online by Cambridge University Press:  05 October 2014

By
Philip Parker ,
Gabriel Nagy ,
Ulrich Trautwein  and
Oliver Lüdtke
Edited by
Ingrid Schoon  and
Jacquelynne S. Eccles
Philip Parker
Affiliation:
Centre for Positive Psychology and Education (CPPE)
Gabriel Nagy
Affiliation:
Leibniz Institute for Science and Mathematics Education (IPN)
Ulrich Trautwein
Affiliation:
University of Tübingen
Oliver Lüdtke
Affiliation:
Humboldt University of Berlin
Ingrid Schoon
Affiliation:
Institute of Education, University of London
Jacquelynne S. Eccles
Affiliation:
University of Michigan, Ann Arbor
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Summary

Abstract

Science, technology, engineering, and mathematics university majors are critical pathways toward prestigious careers, yet women are still underrepresented in many of these domains. In this chapter, we review the role that self-beliefs play in the development of educational aspirations and attempts to realize those aspirations at the end of secondary school. In particular, we use the internal/external frame of reference model to explore the potential of achievement and self-concept profiles as predictors of university major aspirations and attainment as one possible explanation for gender differences in these domains. After reviewing previous research in this area, we provide a research example using a large longitudinal database from Germany (N = 1,881). Results suggest that (a) high math achievement and self-concept predicted math-intensive university major choice and lower likelihood of entering verbal-intensive majors (and vice versa); (b) there appeared to be a continuum of university majors such that strong mathematics achievement and self-concept profiles predicted entry into hard sciences, while the opposite profile predicted entry into the humanities with biology and medicine displaying more mixed patterns; and (c) after controlling for achievement and self-concept there were still important gender differences in university majors. Implications for theory and practice are discussed.

Type
Chapter
Information
Gender Differences in Aspirations and Attainment
A Life Course Perspective
 , pp. 224 - 246
Publisher: Cambridge University Press
Print publication year: 2014

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References

Bandura, A., Barbaranelli, C., Caprara, G. V., & Pastorelli, C. (2001). Self-efficacy beliefs as shapers of children’s aspirations and career trajectories. Child Development, 72, 187–206.CrossRefGoogle ScholarPubMed
Baumert, J., Bos, W., & Lehmann, R. (Eds.). (2000). TIMSS/III. 2: Mathematische und physikalische Kompetenzen am Ende der gymnasialen Oberstufe (Vol. 2). Opladen: Leske + Budrich.
Bowen, W. G., Chingos, M. M., & McPherson, M. S. (2009). Crossing the finish line: Completing college at America’s public universities. Princeton University Press.Google Scholar
Brotman, J., & Moore, F. (2008). Girls and science: A review of four themes in the science education literature. Journal of Research in Science Teaching, 45, 971–1002.CrossRefGoogle Scholar
Camp, A., Gilleland, D., Pearson, C., & Vander Putten, J. (2009). Women’s path into science and engineering majors: A structural equation model. Educational Research and Evaluation, 15, 63–77.CrossRefGoogle Scholar
Chinn, P. (1999). Multiple worlds/mismatched meanings: Barriers to minority women engineers. Journal of Research in Science Teaching, 36, 621–636.3.0.CO;2-V>CrossRefGoogle Scholar
Chow, A., & Salmela-Aro, K. (2011). Task-values across subject domains: A gender comparison using a person-centered approach. International Journal of Behavioral Development, 35, 202–209.CrossRefGoogle Scholar
Eccles, J. (1994). Understanding women’s educational and occupational choices. Psychology of Women Quarterly, 18, 585–609.CrossRefGoogle Scholar
Eccles, J., & Harold, R. (1992). Gender differences in educational and occupational patterns among the gifted. In Colangelo, N., Assouline, S., & Amronson, D. (Eds.), Talent development: Proceedings from the 1991 Henry B. and Jocelyn Wallace National Research Symposium on Talent Development (pp. 3–29). Unionville, NY: Trillium Press.Google Scholar
Elias, P. (1997). Occupational classification (ISCO-88): Concepts, methods, reliability, validity and cross-national comparability. OECD Labour Market and Social Policy Occasional Papers.CrossRef
Jones, M., Howe, A., & Rua, M. (2000). Gender differences in students’ experiences, interests, and attitudes toward science and scientists. Science Education, 84, 180–192.3.0.CO;2-X>CrossRefGoogle Scholar
Keeves, J., & Kotte, D. (1992). Disparities between the sexes in science education: 1970–84. In Keeves, J. (Ed.), The IEA study of science III (pp. 141–164). New York: Pergamon.Google Scholar
Lubinski, D., & Benbow, C. P. (2006). Study of mathematically precocious youth after 35 years: Uncovering antecedents for the development of math-science expertise. Perspectives on Psychological Science, 1, 316–345.CrossRefGoogle ScholarPubMed
Ma, X., & Johnson, W. (2008). Mathematics as the critical filter: Curricular effects on gendered career choices. In Watt, H. & Eccles, J. (Eds.), Gender and occupational outcomes: Longitudinal assessments of individual, social, and cultural influences. Washington, DC: American Psychological Association.Google Scholar
Marsh, H. (1986). Verbal and math self-concepts: An internal/external frame of reference model. American Educational Research Journal, 23, 129.CrossRefGoogle Scholar
Marsh, H. (1990a). Influences of internal and external frames of reference on the formation of math and English self-concepts. Journal of Educational Psychology, 82, 107–116.CrossRefGoogle Scholar
Marsh, H. (1990b). A multidimensional, hierarchical model of self-concept: Theoretical and empirical justification. Educational Psychology Review, 2, 77–172.CrossRefGoogle Scholar
Marsh, H., & Hau, K. (2004). Explaining paradoxical relations between academic self-concepts and achievements: Cross-cultural generalizability of the internal/external frame of reference predictions across 26 countries. Journal of Educational Psychology, 96, 56–67.CrossRefGoogle Scholar
Marsh, H. W., & O’Neill, R. (1984). Self description questionnaire III: The construct validity of multidimensional self-concept ratings by late adolescence. Journal of Educational Psychology, 21, 153–174.Google Scholar
Marsh, H., Trautwein, U., Lüdtke, O., Köller, O., & Baumert, J. (2006). Integration of multidimensional self-concept and core personality constructs: Construct validation and relations to well-being and achievement. Journal of Personality, 74, 403–456.CrossRefGoogle ScholarPubMed
Marsh, H., & Yeung, A. (1997). Coursework selection: Relations to academic self-concept and achievement. American Educational Research Journal, 34, 691.CrossRefGoogle Scholar
Marsh, H.Yeung, A. (2001). An extension of the internal/external frame of reference model: A response to Bong (1998). Multivariate Behavioral Research, 36, 389–420.CrossRefGoogle Scholar
Nagengast, B., Marsh, H. W., Scalas, L. F., Xu, M. K., Hau, K. T., & Trautwein, U. (2011). Who took the “×” out of expectancy-value theory? A psychological mystery, a substantive-methodological synergy, and a cross-national generalization. Psychological science, 22, 1058–1066.CrossRefGoogle Scholar
Nagy, G., Garrett, J., Trautwein, U., Cortina, K., Baumert, J., & Eccles, J. (2008). Gendered high school course selection as a precursor of gendered careers: The mediating role of self-concept and intrinsic value. In Watt, H. & Eccles, J. (Eds.), Gender and occupational outcomes: Longitudinal assessments of individual, social, and cultural influences (pp. 115–143). Washington, DC: American Psychological Association.CrossRefGoogle Scholar
Nagy, G., Trautwein, U., Baumert, J., Köller, O., & Garrett, J. (2006). Gender and course selection in upper secondary education: Effects of academic self-concept and intrinsic value. Educational Research and Evaluation, 12, 323–345.CrossRefGoogle Scholar
OECD. (2004). Education at a glance: OECD indicators. Paris: OECD.Google Scholar
OECD (2011). Learning for tomorrow’s world: First results from PISA 2003. Paris: OECD.Google Scholar
O Mara, A., Marsh, H., Craven, R., & Debus, R. (2006). Do self-concept interventions make a difference? A synergistic blend of construct validation and meta-analysis. Educational Psychologist, 41, 181–206.CrossRefGoogle Scholar
Parker, P. D., Marsh, H. W., Ciarrochi, J., Marshall, S., & Abduljabbar, A. S. (2014). Juxtaposing math self-efficacy and self-concept as predictors of long-term achievement outcomes. Educational Psychology, 43(1), 29–48.CrossRefGoogle Scholar
Parker, P. D., Marsh, H. W., Lüdtke, O., & Trautwein, U. (2013). Differential school contextual effects for math and English: Integrating the Big-Fish-Little-Pond Effect and the Internal/external Frame of Reference. Learning and Instruction, 23, 78–89.CrossRefGoogle Scholar
Parker, P. D., Schoon, I., Tsai, Y.-M., Nagy, G., Trautwein, U., & Eccles, J. S. (2012). Achievement, agency, gender, and socioeconomic background as predictors of postschool choices: A multicontext study. Developmental Psychology, 48(6), 1629–1642. doi: .CrossRefGoogle ScholarPubMed
Rosenbloom, J., Ash, R., Dupont, B., & Coder, L. (2008). Why are there so few women in information technology? Assessing the role of personality in career choices. Journal of Economic Psychology, 29, 543–554.CrossRefGoogle Scholar
Schoon, I. (2001). Teenage job aspirations and career attainment in adulthood: A 17-year follow-up study of teenagers who aspired to become scientists, health professionals, or engineers. International Journal of Behavioral Development, 25, 124–132.CrossRefGoogle Scholar
Schoon, I., Ross, A., & Martin, P. (2007). Science related careers: Aspirations and outcomes in two British cohort studies. Equal Opportunities International, 26, 129–143.CrossRefGoogle Scholar
Schwanzer, A., Trautwein, U., Lüdtke, O., & Sydow, H. (2005). Entwicklung eines Instruments zur Erfassung des Selbstkonzepts junger Erwachsener. Diagnostica, 51, 183–194.CrossRefGoogle Scholar
Sells, L. (1976). The mathematics filter and the education of women and minorities. Paper presented at the Annual Meeting of the American Association for the Advancement of Science, Boston, MA.
Sells, L. (1980). Mathematics: The invisible filter. Engineering Education, 70, 340–341.Google Scholar
Shapka, J., Domene, J., & Keating, D. (2006). Trajectories of career aspirations through adolescence and young adulthood: Early math achievement as a critical filter. Educational Research and Evaluation, 12, 347–358.CrossRefGoogle Scholar
Shavelson, R. J., Hubner, J. J., & Stanton, G. C. (1976). Self-concept: Validation of construct interpretations. Review of Educational Research, 46, 407–441.CrossRefGoogle Scholar
Wigfield, A., Battle, A., Keller, L., & Eccles, J. (2002). Sex differences in motivation, self-concept, career aspiration, and career choice: Implications for cognitive development. In McGillicuddy-De Lisi, A. & De Lisi, R. (Eds.), Biology, society, and behavior: The development of sex differences in cognition (pp. 93–124). Greenwich, CT: Ablex.Google Scholar

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