Math self-concept (MSC) is considered an important predictor of the pursuit of science, technology, engineering and math (STEM) fields. Women’s underrepresentation in the STEM fields is often attributed to their consistently lower ratings on MSC relative to men. Research in this area typically considers STEM in the aggregate and does not account for variations in MSC that may exist between STEM fields. Further, existing research has not explored whether MSC is an equally important predictor of STEM pursuit for women and men. This paper uses a national sample of male and female entering college students over the past four decades to address how MSC varies across STEM majors over time, and to assess the changing salience of MSC as a predictor of STEM major selection in five fields: biological sciences, computer science, engineering, math/statistics, and physical sciences. Results reveal a pervasive gender gap in MSC in nearly all fields, but also a great deal of variation in MSC among the STEM fields. In addition, the salience of MSC in predicting STEM major selection has generally become weaker over time for women (but not for men). Ultimately, this suggests that women’s lower math confidence has become a less powerful explanation for their underrepresentation in STEM fields.
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Among the students included in the survey, 44 % attended public colleges and universities, 31 % were enrolled at private religious institutions, and the remaining 25 % attended private non-sectarian institutions.
To categorize which majors qualified as “STEM,” we took a twofold approach. First, we examined the National Center for Educational Statistics (NCES) Classification of Instructional Programs (NCES 2002), which helped us to narrow our broad list of majors into categories (noted in Appendix Table 4). Next, we examined these categories in concert with extant literature and prevailing definitions as used by the National Science Foundation (NSF) and the Department of Homeland Security (DHS) (Gonzalez and Kuenzi 2012). In doing so, we determined our list of STEM fields to include the five mentioned in the text, which are the most frequently used categories of STEM across these sources.
We opted to run binomial logistic regression because our interest was in the choice of each STEM major relative to all other STEM majors; future research may wish to use multinomial logistic regression to differentiate the choice to major in one specific STEM major versus another.
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This research is supported by the National Science Foundation, HRD #1135727.
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Sax, L.J., Kanny, M.A., Riggers-Piehl, T.A. et al. “But I’m Not Good at Math”: The Changing Salience of Mathematical Self-Concept in Shaping Women’s and Men’s STEM Aspirations. Res High Educ 56, 813–842 (2015). https://doi.org/10.1007/s11162-015-9375-x
- Mathematical self-concept
- Major selection