Using data from a nationally representative, longitudinal survey of college graduates, this study examines student transition from college to their chosen career paths and identifies factors influencing college graduates’ choosing an occupation related to ones’ undergraduate major. Within the context of expanded econometric framework a wide range of variables are considered, including monetary and nonmonetary costs and benefits as well as cultural and social capital measures. Using multinomial logit regression analyses, the results suggest positive career outcomes associated with individuals who have an occupation closely related to their college major, such as a better income profile and greater job satisfaction. Major-based differences are also examined between STEM and non-STEM graduates, and patterns of changes are documented for 10 years after graduation. An important perspective offered by this study is to consider career outcome as an extended definition of institutional effectiveness and student success. Based on the empirical findings, policy implications are discussed with the hope of bringing attention and improvement to the relationship between the higher educational system and the labor market.
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In order to generate the major/job congruency measure for 2003, a 3-step approach was taken: (1) student’s response was copied from 1997 to 2003 if the individual answered “no” to the question on the 2003 survey whether s/he had “more than one career in the last 10 years;” (2) Similarly, student’s response was copied from 1997 to 2003 if an individual’s answer was greater than “5” to the question on the 2003 survey how many “years pursuing career in the industry.” At this point, an unweighted sample size of 5995 out of 8969 (weighted percentage was approximately 67.5 %) had a valid value for the major/job congruency. (3) In the last step, a Bayesian network (BN) was constructed to model the relationship between major/job congruence and a list of related measures (e.g., gender, cumulative GPA in undergraduate major, STEM versus non-STEM undergraduate major, undergraduate major in 12 categories, and occupation in 2003) for the 5995 individuals, and the final BN model had a prediction accuracy of 80 %. The BN model was then applied to the remaining 2974 individuals to predict their major/job congruency.
Austin, A., & Austin, H. (1993). Undergraduate science education: The impact of different college environment and the educational pipeline in the college. Final report. ED 362 404.
Behrman, J., Kletzer, L., McPherson, M., & Schapiro, M. O. (1998). Microeconomics of college choice, careers, and wages. Annals of the American Academy of Political and Social Science, 559, 12–23.
Bourdieu, P., & Passeron, J. C. (1977). Reproduction in education, society, and culture. London: Sage.
Bourdieu, P., & Passeron, J. C. (1979). The inheritors: French students and their relations to culture. Chicago: University of Chicago Press.
Cabrera, A. F. (1994). Logistic regression analysis in higher education: An applied perspective. Higher Education: In J. C. Smart (Ed.), Handbook for the study of higher education (Vol. 10). New York, NY: Agathon Press.
Campbell, G., Denes, R., & Morrison, C. (2000). Access denied: Race, ethnicity, and the scientific enterprise. Oxford: Oxford University Press.
Chang, M. J., Eagan, M. K., Lin, M. H., & Hurtado, S. (2011). Considering the impact of racial stigmas and science identity: Persistence among biomedical and behavioral science aspirants. The Journal of Higher Education, 82(5), 564–596.
Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94(Supplement), 95–120.
Ehrenberg, R. G. (1991). Academic labor supply. In C. T. Clotfelter, R. G. Ehrenberg, M. Getz, & J. J. Siegfried (Eds.), Economic challenges in higher education (pp. 143–260). Chicago: University of Chicago Press.
Ethington, C. A., & Smart, J. C. (1986). Persistence to graduate education. Research in Higher Education, 24(3), 287–303.
Flyer, F. A. (1997). The influence of higher moments of earnings distributions of career decisions. Journal of Labor Economics, 15(4), 689–713.
Fox, M. (1992). Student debt and enrollment in graduate and professional school. Applied Economics, 24, 669–677.
Frehill, L. M., Di Fabio, N. M., & Hill, S. T. (2008). Confronting the ‘‘new’’ American dilemma. White Plains National Action Council for Minorities in Engineering. Retrieved February 19, 2012 from http://www.nacme.org/user/docs/NACME%2008%20ResearchReport.pdf
Goyette, K. A., & Mullne, A. L. (2006). Who studies the arts and sciences? Social background and the Choice and consequences of undergraduate field of study. The Journal of Higher Education, 77(3), 497–538.
Griffith, A. L. (2010). Persistent of women and minorities in the STEM field majors: Is it the school that matters. Economics of Education Review, 29, 911–922.
Hosmer, D., & Lemeshow, S. (2000). Applied logistic regression analysis (2nd ed.). New York, NY: Wiley.
Hurtado, S., Eagan, M. K., Cabrera, N. L., Lin, M. H., Park, J., & Lopez, M. (2008). Training future scientists: Predicting first-year minority student participation in health science research. Research in Higher Education, 49(2), 126–152.
Hurtado, S., Han, J. C., Sae′nz, V. B., Espinosa, L. L., Cabrera, N. L., & Cerna, O. S. (2007). Predicting transition and adjustment to college: Biomedical and behavioral science aspirants’ and minority students’ first year of college. Research in Higher Education, 48(7), 841–887.
Ishida, H., Spilerman, S., & Su, K. (1997). Educational credentials and promotion changes in Japanese and American organizations. American Sociological Review, 62(6), 866–882.
Jackson, G. A. (1990). Financial aid, college entry, and affirmative action. American Journal of Education, 98, 523–550.
Jacobs, J. A. (1986). The sex-segregation of fields of study: Trends during the college years. Journal of Higher Education, 57(2), 134–154.
Jacobs, J. A. (1995). Gender and academic specialties: Trends among recipients of college degrees in the 1980 s. Sociology of Education, 68(2), 81–98.
Joy, L. (2000, May). Do colleges shortchange women? Gender differences in the transition from college to work. Papers and proceedings of the one hundred twelfth annual meeting of the American economic association (pp. 471–475).
Keane, M. P., & Wolpin, K. I. (1997). The career decisions of young men. Journal of Political Economy, 105(3), 473–522.
Lamont, M., & Lareau, A. (1988). Cultural capital: Allusions, gaps and glissandos in recent theoretical developments. Sociological Theory, 6, 153–168.
Melguizo, T., & Wolniak, G. (2011). The earnings benefits of majoring in STEM fields among high achieving minority students. Research in Higher Education (online preprint).
Montmarquette, C., Cannings, K., & Mahseredjian, S. (2002). How do young people choose college major? Economics of Education Review, 21, 543–556.
Morrow, V. (1999). Conceptualizing social capital in relation to the well-being of children and young people: A critical review. Sociological Review, 47, 744–765.
Mullen, A. L., Goyette, K. A., & Soares, J. A. (2003). Who goes to graduate school? Social and academic correlates of educational continuation after college. Sociology of Education, 76, 143–169.
Pampel, F. C. (2000). Logistic regression: A primer. In Sage University papers series on quantitative applications in the social sciences, 07-132. Thousand Oaks, CA: Sage Publications.
Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students: A third decade of research. San Francisco: Jossey-Bass.
Peng, C. J., So, T. S. H., Stage, F. K., & St. John, E. P. (2002). The use and interpretation of logistic regression in higher education journals. Research in Higher Education, 43, 259–294.
Perna, L. W. (2000). Differences in the decision to enroll in college among African Americans, Hispanics, and Whites. Journal of Higher Education, 71, 117–141.
Perna, L. W. (2004). Understanding the decision to enroll in graduate school: Sex and racial/ethnic group differences. The Journal of Higher Education, 75(5), 487–527.
Roksa, J. (2005). Double disadvantage or blessing in disguise? Understanding the relationship between college major and employment sector. Sociology of Education, 78(3), 207–232.
Roksa, J., & Levey, T. (2010). What can you do with that degree? College major and occupational status of college graduates over time. Social Forces, 89, 389–416.
Sax, L. J. (2001). Undergraduate science majors: Gender differences in who goes to graduate school. The Review of Higher Education, 24(2), 153–172.
Seibert, S. E., Kraimer, M. L., & Liden, R. C. (2001). A social capital theory of career success. The Academy of Management Journal, 44(2), 219–237.
Simpson, J. C. (2001). Segregated by subject: Racial differences in the factors influencing academic major between European Americans, Asian Americans, and African, Hispanic, and Native Americans. Journal of Higher Education, 72(1), 63–100.
Smart, J. C. (1986). College effects on occupational status attainment. Research in Higher Education, 24(1), 73–95.
Smart, J. C. (1988). College influences on graduates’ income levels. Research in Higher Education, 29, 41–59.
Staniec, J. F. O. (2004). The effects of race, sex, and expected returns on the choice of college major. Eastern Economic Journal, 30(4), 549–562.
Stoecker, J. L., & Pascarella, E. T. (1991). Women’s college and women’s career attainments revisited. Journal of Higher Education, 62(4), 394–406.
Stolzenberg, R. M. (1994). Educational continuation by college graduates. American Journal of Sociology, 99, 1042–1077.
Thomas, S. L., & Heck, R. H. (2001). Analysis of large-scale secondary data in higher education research: Potential perils associated with complex sampling designs. Research in Higher Education, 42(5), 517–540.
Thomas, S. L., & Zhang, L. (2005). Post-baccalaureate wage growth within 4 years of graduation: The effects of college quality and college major. Research in Higher Education, 46(4), 437–459.
Weiler, W. C. (1991). The effect of undergraduate student loans on the decision to pursue post-baccalaureate study. Educational Evaluation and Policy Analysis, 13, 212–220.
Wells, R. (2008). The effects of social and cultural capital on student persistence: are community colleges more meritocratic? Community College Review, 36(1), 25–46.
Whalen, D. F., & Shelley, M. C. (2010). Academic success for STEM and non-STEM majors. Journal of STEM Education, 11(1–2), 45–60.
Wolniak, G. C., & Pascarella, E. T. (2005). The effects of college major and job field congruence on job satisfaction. Journal of Vocational Behavior, 67, 233–251.
Zhang, L. (2005). Advance to graduate education: The effect of college quality and undergraduate majors. The Review of Higher Education, 28(3), 313–338.
This material is based upon work supported by the Association for Institutional Research, the National Center for Education Statistics, the National Science Foundation, and the National Postsecondary Education Cooperative under Association for Institutional Research Grant Number RG11-12.
Exploratory factor analysis of the fourteen items on career aspiration
|Initial extraction||Factor loading|
|CHOICE01 Job choice depends on previous work experience||0.428||0.654|
|CHOICE02 Job choice depends on good starting income||Excluded|
|CHOICE03 Job choice depends on good income potential||0.240||0.490|
|CHOICE04 Job choice depends on job security||0.367||0.606|
|CHOICE05 Job choice depends on prestige and status||0.324||0.569|
|CHOICE06 Job choice depends on interesting work||0.378||0.614|
|CHOICE07 Job choice depends on intellectual work||0.313||0.560|
|CHOICE08 Job choice depends on freedom at work||0.661||0.813|
|CHOICE09 Job choice depends on interaction with people||0.429||0.655|
|CHOICE10 Job choice depends on working independently||0.587||0.766|
|CHOICE11 Job choice depends on travel||Excluded|
|CHOICE12 Job choice depends on ability to be established||0.448||0.670|
|CHOICE13 Job choice depends on time for other activities||0.575||0.758|
|CHOICE14 Job choice depends on other considerations||Excluded|
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Xu, Y.J. Career Outcomes of STEM and Non-STEM College Graduates: Persistence in Majored-Field and Influential Factors in Career Choices. Res High Educ 54, 349–382 (2013). https://doi.org/10.1007/s11162-012-9275-2
- Career outcome
- College graduates
- Differences in STEM and non-STEM disciplines