14 SES 04.5 PS, General Poster Session
General Poster Session
As the world continues to advance technologically, increasing the interest in and persistence of secondary students in STEM fields has become a key policy focus for national governments across the globe. Previous research has suggested that for students who choose to pursue postsecondary education in STEM fields do so because of interest in math or science as opposed to merely how they perform on achievement tests (Maltese & Tai, 2011). This points to the idea that increasing interest in STEM fields may be a promising policy lever to boost STEM participation. It is understood that parents can play a key role in focusing student interest, and may therefore be a strong factor in promoting STEM participation. With this relationship between parent and student in mind, we conducted a literature synthesis to answer the following questions:
- Within the body of literature, what is the association between parent professionalism, and math/science achievement and college major choice?
- Within the body of literature, what is the association between parent STEM occupation, and STEM interests/motivations/achievement, college major, and career choices?
- Are there differences in these relationships by gender or racial/ethnic background?
In this study, we explore whether characteristics of parents’ occupations lead their children to high achievement and interest in STEM fields. While we focus on adolescents’ educational outcomes (rather than occupational outcomes), literature on the transmission of occupations and social class across generations is relevant, as children’s educational preparation is a key mediating mechanism. The transmission of occupations across generations has been studied by social stratification and class mobility scholars for decades, including seminal work by Blau & Duncan (1967). Past research has distinguished between “big classes,” “gradational classes,” and, more recently “microclasses,” with each definition of class relying on characteristics of occupations (Jonsson, Di Carlo, Brinton, Grusky, & Pollak, 2009; Treiman, 1976; Weeden & Grusky, 2012; Wright, 1980). Big class perspectives argue that aggregate occupational categories such as professional, manager, service worker, and laborer delineate key inequalities between social classes. Gradational approaches rely on an indicator of socioeconomic status (SES) prestige, which is associated with occupation, to distinguish between occupations. Microclass research argues that distinctions occur at a lower level of aggregation—discrete institutionalized occupations (e.g., doctor, professor, lab researcher). Each perspective provides rationale for how and why adolescents whose parents are employed in professional or STEM occupation may pursue advanced STEM coursework, select STEM college majors, or perform well on STEM achievement tests.
First, the big class perspective suggests that children tend to end up in the same occupational class as their parents, pursuing appropriate educational outcomes along the way. Second, the gradational perspective takes a more fine-grained approach, suggesting that children inherit their parents’ SES and prestige, also via economic resources, social networks, and cultural resources like socialization. STEM occupations tend to be highly paid and score high on occupational prestige scales (though there is debate about the components of such scales) (Hauser & Warren, 1997; Langdon, McKittrick, Beede, Khan, & Doms, 2011). Third, the microclass perspective is similar to the big class perspective in arguing that children adopt class-specific tastes, skills, and networks, but they define class much more narrowly, on the basis of specific occupations. Overall, past research on the transmission of social class and occupations indicates that children of professional parents and those employed in STEM occupations may have greater achievement in and orientation to STEM education.
Biecek, P., & Borgonovi, F. (2014). Do parents’ occupations have an impact on student performance? Pisa in Focus, 36, 1–4. Dabney, K. P., Chakraverty, D., & Tai, R. H. (2013). The association of family influence and initial interest in science. Science Education, 97(3), 395–409. Haile, G. A., & Nguyen, A. N. (2008). Determinants of academic attainment in the United States: A quantile regression analysis of test scores. Education Economics, 16(1), 29–57. Hampden-Thompson, G., & Johnston, J. S. (2006). Variation in relationship between non-school factors and student achievement on international assessments. Washington, D.C. Harwell, E. (2012). An analysis of parent occupation and student choice in STEM major. Kjaernsli, M., & Lie, S. (2011). Students’ preference for science careers: Internatioanal comparisons based on PISA 2006. International Journal of Science Education, 33(1), 121–144. Leppel, K., Williams, M. L., & Waldauer, C. (2001). The impact of parental occupation and socioeconomic status on choice of college major. Journal of Family and Economic Issues, 22(4), 373–394. Leslie, L. L., McClure, G. T., & Oaxaca, R. L. (1998). Women and minorities in science and engineering: A life sequence analysis. The Journal of Higher Education, 69(3), 239–275. Maltese, A. V., & Tai, R. H. (2011). Pipeline persistence: Examining the association of educational experiences with earned degrees in STEM among U.S. students. Science Education, 95(5), 877–907. Moakler Jr., M. W., & Kim, M. M. (2014). College major choice in STEM: Revisiting confidence and demographic factors. The Career Development Quarterly, 62, 128–142. OECD. (2007). PISA 2006 science competencies for tomorrow’s world: Volume 1 - Analysis. Paris. Sikora, J., & Pokropek, A. (2012). Intergenerational transfers of preferences for science careers in comparative perspective. International Journal of Science Education, 34(16), 2501–2527. Treiman, D. J. (1976). A Standard Occupational Prestige Scale for Use with Historical Data. The Journal of Interdisciplinary History, 7(2), 283–304. Wang, M.-T., Degol, J., & Ye, F. (2015). Math achievement is important, but task values are critical too: Examining the intellectual and motivational factors leading to disparities in STEM careers. Frontiers in Psychology, 6(36), 1–9. Weeden, K. A., & Grusky, D. B. (2012). The Three Worlds of Inequality. American Journal of Sociology, 117(6), 1723–1785. Wright, E. O. (1980). Class and Occupation. Theory and Society, 9(1), 177–214.
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