Charting career aspirations: a latent class mixture model of aspiration trajectories in childhood and adolescence

Abstract

Young people often are asked what they want to be when they grow up. How do their aspirations change as students move through childhood and adolescence? To investigate the formation of career aspirations, we analysed 6308 questionnaires from 4213 students aged 8 to 18 years arranged in an accelerated longitudinal design. Using a person-centred analytic approach, a latent class mixture model identified four discrete change trajectories in the prestige levels of career aspirations over ten schooling years. In line with Gottfredson’s (J Counsel Psychol 28(6):545–579, 1981) theory, significant factors included student gender, education aspirations, prior achievement, knowledge of educational pathways to occupations, and the sex composition of occupations. High aspiring students with low education aspirations and poor achievement had more volatile trajectories than other students, regardless of socioeconomic status. The results demonstrate complexity in the formation of aspirations and challenge conventional notions about the ‘types’ of students who have ‘high’ and ‘low’ aspirations.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

References

  1. Akos, P., Lambie, G., Milsom, A., & Gilbert, K. (2007). Early adolescents' aspirations and academic tracking: An exploratory investigation. Professional School Counseling, 11(1), 57–64. https://doi.org/10.5330/PSC.n.2010-11.57.

    Article  Google Scholar 

  2. Anderson, E. R. (1995). Accelerating and maximizing information from short-term longitudinal research. In J. M. Gottman (Ed.), The analysis of change (pp. 139–163). Mahwah, NJ: Erlbaum.

    Google Scholar 

  3. Asparouhov, T., & Muthén, B. O. (2014). Auxiliary variables in mixture modelling: Three-step approaches using Mplus. Structural Equation Modeling: A Multidisciplinary Journal, 21(3), 329–341. https://doi.org/10.1080/10705511.2014.915181.

    Article  Google Scholar 

  4. Aunola, K., Selänne, A., Selänne, H., & Ryba, T. (2018). The role of adolescent athletes’ task value patterns in their educational and athletic career aspirations. Learning and Individual Differences, 63, 34–43. https://doi.org/10.1016/j.lindif.2018.03.004.

    Article  Google Scholar 

  5. Australian Bureau of Statistics. (2006). In: D. Trewing & B. Pink (Eds.)ANZSCO—Australian and New Zealand standard classification of occupations. Canberra, Australia: Author.

  6. Bae, C. L., & DeBusk-Lane, M. (2018). Motivation belief profiles in science: Links to classroom goal structures and achievement. Learning and Individual Differences, 67, 91–104. https://doi.org/10.1016/j.lindif.2018.08.003.

    Article  Google Scholar 

  7. Bagilhole, B. (2002). Women in non-traditional occupations: Challenging men. New York, NY: Palgrave Macmillan.

    Book  Google Scholar 

  8. Bardick, A., Bernes, K., Magnusson, K., & Witko, K. (2006). Junior high school students’ occupational aspirations. Alberta Counsellor, 28(2), 3–9.

    Google Scholar 

  9. Beavis, A. (2007). Evidence in support of Gottfredson's common cognitive map of occupations. Australian Journal of Career Development, 16(1), 38–44. https://doi.org/10.1177/103841620701600107.

    Article  Google Scholar 

  10. Bell, R. Q. (1954). An experimental test of the accelerated longitudinal approach. Child Development, 25(4), 281–286. https://doi.org/10.2307/1126058.

    Article  Google Scholar 

  11. Berger, N., Hanham, J., Stevens, C. J., & Holmes, K. (2019). Immediate feedback improves career decision self-efficacy and aspirational alignment. Frontiers in Psychology, 13, 1–5. https://doi.org/10.3389/fpsyg.2019.00255.

    Article  Google Scholar 

  12. Bradley, D., Noonan, P., Nugent, H., & Scales, B. (2008). Review of Australian higher education. Canberra, Australia: Commonwealth of Australia.

    Google Scholar 

  13. Brown, D. (2002). Career choice and development (4th ed.). San Francisco, CA: Jossey-Bass.

    Google Scholar 

  14. Buscot, M., Thomson, R. J., Juonala, M., Sabin, M. A., Burgner, D. P., Lehtimaki, T., et al. (2018). European Heart Journal, 39(24), 2263–2270. https://doi.org/10.1093/eurheartj/ehy161.

    Article  Google Scholar 

  15. Care, E., Deans, J., & Brown, R. (2007). The realism and sex type of four- to five-year-old children's occupational aspirations. Journal of Early Childhood Research, 5(2), 155–168. https://doi.org/10.1177/1476718x07076681.

    Article  Google Scholar 

  16. Chen, Q., Luo, W., Palardy, G. J., Glaman, R., & McEnturff, A. (2017). The efficacy of common fit indices for enumerating classes in growth mixture models when nested data structure is ignored: A Monte Carlo study. SAGE Open, 7(1), 1–19. https://doi.org/10.1177/2158244017700459.

    Article  Google Scholar 

  17. Cochran, D., Wang, E., Stevenson, S., Johnson, L., & Crews, C. (2011). Adolescent occupational aspirations: Test of Gottfredson's theory of circumscription and compromise. The Career Development Quarterly, 59(5), 412–427. https://doi.org/10.1002/j.2161-0045,2011.tb00968.x.

    Article  Google Scholar 

  18. Commonwealth of Australia. (2009). Transforming Australia's higher education system. Canberra, Australia: Author.

    Google Scholar 

  19. Council of Australian Governments. (2010). Education 2010: Comparing performance across Australia. Canberra, Australia: Author.

    Google Scholar 

  20. Daraganova, G., Edwards, B., & Sipthorp, M. (2013). Using National Assessment Program – Literacy and Numeracy (NAPLAN) data in the Longitudinal Study of Australian Children (LSAC). Canberra, Australia: Australian Institute of Family Studies.

    Google Scholar 

  21. Duncan, S. C., Duncan, T. E., & Hops, H. (1996). Analysis of longitudinal data within accelerated longitudinal designs. Psychological Methods, 1(3), 236–248. https://doi.org/10.1037/1082-989X.1.3.236.

    Article  Google Scholar 

  22. Eshghi, A., Haughton, D., Legrand, P., Skaletsky, M., & Woolford, S. (2011). Identifying groups: A comparison of methodologies. Journal of Data Science, 9, 271–291.

    Google Scholar 

  23. Furlong, A., & Biggart, A. (1999). Framing 'choices': A longitudinal study of occupational aspirations among 13- to 16-year-olds. Journal of Education and Work, 12(1), 21–35. https://doi.org/10.1080/1363908990120102.

    Article  Google Scholar 

  24. Gemici, S., Bednarz, A., Karmel, T., & Lim, P. (2014). The factors affecting the educational and occupational aspirations of young Australians. Adelaide, Australia: National Centre for Vocational Education Research.

    Google Scholar 

  25. Goodman, E., Adler, N. E., Kawachi, I., Frazier, A. L., Huang, B., & Colditz, G. A. (2001). Adolescents perceptions of social status: Developmental evaluation of a new indicator. Pediatrics, 108(2), 1–8. https://doi.org/10.1542/peds.108.2.e31.

    Article  Google Scholar 

  26. Gore, J., Holmes, K., Smith, M., Ellis, H., Albright, J., Southgate, E., & Berger, N. (2014). On the relationship between socio-economic status and educational and career aspirations in the middle years of schooling. In Poster session presented at the American Educational Research Association 2014 annual meeting, Philadelphia, PA. https://doi.org/10.13140/RG.2.2.21858.02244.

  27. Gore, J., Holmes, K., Smith, M., Southgate, E., & Albright, J. (2015). Socioeconomic status and the career aspirations of Australian school students: Testing enduring assumptions. Australian Educational Researcher, 42(2), 155–177. https://doi.org/10.1007/s13384-015-0172-5.

    Article  Google Scholar 

  28. Gore, J., Rickards, B., Fray, L., Holmes, K., & Smith, M. (2017a). Profiling Australian school students’ interest in a nursing career: Insights for ensuring the future workforce. Australian Journal of Advanced Nursing, 35(2), 12–22.

    Google Scholar 

  29. Gore, J., Holmes, K., Smith, M., Fray, L., McElduff, P., Weaver, N., & Wallington, C. (2017b). Unpacking the career aspirations of Australian school students: Towards an evidence base for university equity initiatives in schools. Higher Education Research and Development, 36(7), 1383–1400. https://doi.org/10.1080/07294360.2017.1325847.

    Article  Google Scholar 

  30. Gore J., Fray, L., Wallington, C., Holmes, K., & Smith M. (2017c). Australian school student aspirations for military careers: Traditional perceptions in shifting contexts. Armed Forces and Society, 43(2), 238–259. https://doi.org/10.1177/0095327X16682046.

    Article  Google Scholar 

  31. Gottfredson, L. S. (1981). Circumscription and compromise: A developmental theory of occupational aspirations. Journal of Counseling Psychology, 28(6), 545–579. https://doi.org/10.1037/0022-0167.28.6.545.

    Article  Google Scholar 

  32. Gottfredson, L. S. (2002). Gottfredson's theory of circumscription, compromise and self- creation. In D. Brown (Ed.), Career choice and development (4th ed., pp. 85–148). San Francisco, CA: Jossey-Bass.

    Google Scholar 

  33. Gottfredson, L. S. (2005). Using Gottfredson’s theory of circumscription and compromise in career guidance and counseling. In S. D. Brown & R. W. Lent (Eds.), Career development and counseling: Putting theory and research to work (pp. 71–100). Hoboken, NJ: Wiley.

    Google Scholar 

  34. Hannah, J.-A. S., & Kahn, S. E. (1989). The relationship of socioeconomic status and gender to the occupational choices of grade 12 students. Journal of Vocational Behavior, 34(2), 161–178. https://doi.org/10.1016/0001-8791(89)90012-2.

    Article  Google Scholar 

  35. Haughton, D., Legrad, P., & Woolford, S. (2009). Review of three latent class cluster analysis packages: Latent GOLD, poLCA, and MCLUST. The American Statistician, 63(1), 81–91. https://doi.org/10.1198/tast.2009.0016.

    Article  Google Scholar 

  36. Heckhausen, J., & Tomasik, M. J. (2002). Get an apprenticeship before school is out: How German adolescents adjust vocational aspirations when getting close to a developmental deadline. Journal of Vocational Behavior, 60(2), 199–219. https://doi.org/10.1006/jvbe.2001.1864.

    Article  Google Scholar 

  37. Helwig, A. (1998). Gender-role stereotyping: Testing theory with a longitudinal sample. Sex Roles, 38(5–6), 403–423. https://doi.org/10.1023/A:1018757821850.

    Article  Google Scholar 

  38. Helwig, A. (2001). A test of Gottfredson's theory using a ten-year longitudinal study. Journal of Career Development, 28(2), 77–95. https://doi.org/10.1023/a:1012578625948.

    Article  Google Scholar 

  39. Holmes, K., Gore, J. M., Smith, M., & Lloyd, A. (2018). An integrated analysis of school students’ aspirations for STEM careers: Which student and school factors are most predictive? International Journal of Science and Mathematics Education, 16(4), 655–675. https://doi.org/10.1007/s10763-016-9793-z.

    Article  Google Scholar 

  40. Howard, K., Carlstrom, A., Katz, A., Chew, A., Ray, G. C., Laine, L., et al. (2011). Career aspirations of youth: Untangling race/ethnicity, SES, and gender. Journal of Vocational Behavior, 79(1), 98–109. https://doi.org/10.1016/j.jvb.2010.12.002.

    Article  Google Scholar 

  41. Jung, T., & Wickrama, K. A. S. (2008). An introduction to latent class growth analysis and growth mixture modeling. Social and Personality Psychology Compass, 2(1), 302–337. https://doi.org/10.1111/j.1751-9004.2007.00054.x.

    Article  Google Scholar 

  42. Kenway, J., & Hickey-Moody, A. (2011). Life chances, lifestyle and everyday aspirational strategies and tactics. Critical Studies in Education, 52(2), 151–163. https://doi.org/10.1080/17508487.2011.572828.

    Article  Google Scholar 

  43. Khattab, N. (2015). Students' aspirations, expectations and school achievement: What really matters? British Educational Research Journal, 41(5), 731–748. https://doi.org/10.1002/berj.3171.

    Article  Google Scholar 

  44. Lazarides, R., Viljaranta, J., Aunola, K., Pesu, L., & Nurmi, J. E. (2016). The role of parental expectations and students’ motivational profiles for educational aspirations. Learning and Individual Differences, 51, 29–36. https://doi.org/10.1016/j.lindif.2016.08.024.

    Article  Google Scholar 

  45. Lythgoe, D. T., Garcia-Fiñana, M., & Cox, T. (2019). Latent class modelling with a time-to-event distal outcome: A comparison of one, two, and three-step approaches. Structural Equation Modeling: A Multidisciplinary Journal, 26(1), 51–65. https://doi.org/10.1080/10705511.2018.1495081.

    Article  Google Scholar 

  46. Marjoribanks, K. (2002). Family contexts, individual characteristics, proximal settings, and adolescents' aspirations. Psychological Reports, 91(3), 769–779. https://doi.org/10.2466/pr0.2002.91.3.769.

    Article  Google Scholar 

  47. Mau, W., & Bikos, L. (2000). Educational and vocational aspirations of minority and female students: A longitudinal study. Journal of Counseling Development, 78(2), 186–194. https://doi.org/10.1002/j.1556-6676.2000.tb02577.x.

    Article  Google Scholar 

  48. McMillan, J., Beavis, A., & Jones, F. L. (2009). The AUSEI06: A new socioeconomic index for Australia. Journal of Sociology, 45(2), 123–149. https://doi.org/10.1177/1440783309103342.

    Article  Google Scholar 

  49. Michaelides, M. P., Brown, G. T. L., Eklöf, H., & Papanastasiou, E. C. (2019). Introduction to motivational profiles in TIMSS mathematics. In M. P. Michaelides, G. T. L. Brown, H. Eklöf, & E. C. Papanastasiou (Eds.), Motivational profiles in TIMSS mathematics: Exploring student clusters across countries and time (pp. 1–7). Cham, Switzerland: Springer.

    Chapter  Google Scholar 

  50. Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14(4), 535–569. https://doi.org/10.1080/10705510701575396.

    Article  Google Scholar 

  51. Patton, W., & Creed, P. (2007). The relationship between career variables and occupational aspirations and expectations for Australian high school adolescents. Journal of Career Development, 34(2), 127–148. https://doi.org/10.1177/0894845307307471.

    Article  Google Scholar 

  52. Perry, B. L., Martinez, E., Morris, E., Link, T. C., & Leukefeld, C. (2016). Misalignment of career and educational aspirations in middle school: Differences across race, ethnicity, and socioeconomic status. Social Science, 5(3), 35–45. https://doi.org/10.3390/socsci5030035.

    Article  Google Scholar 

  53. Powers, R., & Wojtkiewicz, R. (2004). Occupational aspirations, gender, and educational attainment. Sociological Spectrum, 24(5), 601–622. https://doi.org/10.1080/02732170490448784.

    Article  Google Scholar 

  54. Prinzie, P., & Onghena, P. (2005). Cohort sequential design. In B. S. Everitt & D. C. Howell (Eds.), Encyclopedia of statistics in behavioral science (Vol. 1, pp. 319–322). Chichester, United Kingdom: Wiley.

    Google Scholar 

  55. Proust-Lima, C., Philipps, V., & Liquet, B. (2017). Estimation of extended mixed models using latent classes and latent processes: The R package lcmm. Journal of Statistical Software, 78(2), 1–56. https://doi.org/10.18637/jss.v078.i02.

    Article  Google Scholar 

  56. Proust-Lima, C., Sene, M., Taylor, J. M. G., & Jacqmin-Gadda, H. (2012). Joint latent class models for longitudinal and time-to-event data: A review. Statistical Methods in Medical Research, 23(1), 74–90. https://doi.org/10.1177/0962280212445839.

    Article  Google Scholar 

  57. Raftery, A. E. (1995). Bayesian model selection in social research. Sociological Methodology, 25, 111–163. https://doi.org/10.2307/271063.

    Article  Google Scholar 

  58. Rojewski, J., & Kim, H. (2003). Career choice patterns and behavior of work-bound youth during early adolescence. Journal of Career Development, 30(2), 89–108. https://doi.org/10.1177/089484530303000201.

    Article  Google Scholar 

  59. Schoon, I., & Parsons, S. (2002). Teenage aspirations for future careers and occupational outcomes. Journal of Vocational Behavior, 60(2), 262–288. https://doi.org/10.1006/jvbe.2001.1867.

    Article  Google Scholar 

  60. Schreiber, J. B., & Pekarik, A. J. (2014). Technical note: Using latent class analysis versus k-means or hierarchical clustering to understand museum visitors. Curator: The Museum Journal, 57(1), 45–59. doi:10.1111/cura.12050

  61. Shapka, J. D., Domene, J. F., & Keating, D. P. (2006). Trajectories of career aspirations through adolescence and young adulthood: Early math achievement as a critical filter. Educational Research and Evaluation, 12(4), 347–358. https://doi.org/10.1080/13803610600765752.

    Article  Google Scholar 

  62. Sheldrake, R., Mutjaba, T., & Reiss, M. J. (2017). Students’ changing attitudes and aspirations towards physics during secondary school. Research in Science Education. https://doi.org/10.1007/s11165-017-9676-5.

    Article  Google Scholar 

  63. Sirin, S. R., Diemar, M. A., Jackson, L. R., Gonsalves, L., & Howell, A. (2004). Future aspirations of urban adolescents: A person-in-context model. International Journal of Qualitative Studies in Education, 17(3), 437–456. https://doi.org/10.1080/0951839042000204607.

    Article  Google Scholar 

  64. St Clair, R., & Benjamin, A. (2011). Performing desires: The dilemma of aspirations and educational attainment. British Educational Research Journal, 37(3), 501–517. https://doi.org/10.1080/01411926.2010.481358.

    Article  Google Scholar 

  65. Vermunt, J. K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18(4), 450–469. https://doi.org/10.1093/pan/mpq025.

    Article  Google Scholar 

  66. Walkey, F. H., McClure, J., Meyer, L. H., & Weir, K. F. (2013). Low expectations equal no expectations: Aspirations, motivation, and achievement in secondary school. Contemporary Educational Psychology, 38(4), 306–315. https://doi.org/10.1016/j.cedpsych.2013.06.004.

    Article  Google Scholar 

  67. Wang, M., & Bodner, T. E. (2007). Growth mixture modeling: Identifying and predicting unobserved subpopulations with longitudinal data. Organizational Research Methods, 10(4), 635–656. https://doi.org/10.1177/1094428106289397.

    Article  Google Scholar 

  68. Watt, H. M. G., Bucich, M., & Dacosta, L. (2019). Adolescents’ motivational profiles in mathematics and science: Associations with achievement striving, career aspirations and psychological wellbeing. Frontiers in Psychology, 10, 1–23. https://doi.org/10.3389/fpsyg.2019.00990.

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Nathan Berger.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Berger, N., Holmes, K., Gore, J.M. et al. Charting career aspirations: a latent class mixture model of aspiration trajectories in childhood and adolescence. Aust. Educ. Res. 47, 651–678 (2020). https://doi.org/10.1007/s13384-019-00363-x

Download citation

Keywords

  • Career aspirations
  • Gottfredson’s theory
  • School students
  • Accelerated longitudinal design