This article uses an added value measure to assess the gender-specific impact of attending a STEM (Science, Technology, Engineering and Math) program. Using the results of the mandatory Colombian national exit exams, we compare the math and reading scores at the end of high school and at the end of college by gender. A difference-in-differences technique combined with propensity score matching is used to address selection bias. We find that the gender-related achievement gap in math and reading scores increases after college affecting women. The gap is larger for those individuals studying a STEM major in comparison with a non-STEM major. Moreover, we find that the gender gap is higher in public and accredited universities.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Law 3963 of 2009, enacted by Colombian Ministry of Education.
Technical and technological programs are different from professional programs in terms of duration and learning goals. The first having a duration between 1.5 to 3 years whereas professionals between 4 to 6. Moreover, technical and technological programs are mainly offered by technical institutions instead of universities and they emphasis in applications more than theory and research.
For a comprehensive review of value-added models, including its benefits and limitations, please refer to Koedel et al. (2015).
van de Walle and Mu (2007) use this approach to estimate the impact of rural road rehabilitation on market development at the commune level in rural Vietnam.
Abadía, L. K. (2017). Gender score gap of Colombian students in the pisa test. Vniversitas Economicas, 17(8).
Abadía, L. K., & Bernal, G. (2017). A widening gap? A gender-based analysis of performance on the Colombian high school exit examination. Revista de Economía del Rosario, 20(1), 5–31.
Ackerman, P. L., Kanfer, R., & Calderwood, C. (2013). High school advanced placement and student performance in college: STEM majors, non-STEM majors, and gender differences. Teachers College Record, 115(10), 100305.
Ayalon, H. (2003). Women and men go to university: mathematical background and gender differences in choice of field in higher education. Sex Roles, 48(5–6), 277–290. https://doi.org/10.1023/A:1022829522556.
Balcazar, C. F., & Ñopo, H. (2016). Broken gears: the value added of higher education on teachers’ academic achievement. Higher Education, 72(3), 341–361. https://doi.org/10.1007/s10734-015-9960-0.
Baldiga, K. (2013). Gender differences in willingness to guess. Management Science, 60(2), 434–448.
Beede, D. N., Julian, T. A., Langdon, D., McKittrick, G., Khan, B., & Doms, M. E. (2011). Women in STEM: a gender gap to innovation. Economics and Statistics Administration Issue Brief, 04–11.
Bielby, R., Posselt, J. R., Jaquette, O., & Bastedo, M. N. (2014). Why are women underrepresented in elite colleges and universities? A non-linear decomposition analysis. Research in Higher Education, 55(8), 735–760. https://doi.org/10.1007/s11162-014-9334-y.
Brown, J. L., Halpin, G., & Halpin, G. (2015). Relationship between high school mathematical achievement and quantitative GPA. Higher Education Studies, 5(6), 1–8. https://doi.org/10.5539/hes.v5n6p1.
Buschor, C. B., Berweger, S., Frei, A. K., & Kappler, C. (2014). Majoring in STEM-what accounts for women’s career decision making? A mixed methods study. Journal of Educational Research, 107(3), 167–176. https://doi.org/10.1080/00220671.2013.788989.
Caliendo, M., & Kopeinig, S. (2005). Some practical guidance for the implementation of propensity score matching. In IZA Discussion Paper No. 1588. Bonn: The Institute for the Study of Labor.
Carrell, S. E., Page, M. E., & West, J. E. (2010). Sex and science: how professor gender perpetuates the gender gap. The Quarterly Journal of Economics, 125(3), 1101–1144.
Castillo, R., & Montes-Berges, B. (2014). Analysis of current gender stereotypes. Anales de Psicología, 30(3), 1044–1060. https://doi.org/10.6018/analesps.30.3.138981.
Clark Blickenstaff, J., & Blickenstaff, J. C. (2005). Women and science careers: leaky pipeline or gender filter? Gender and Education, 17(4), 369–386. https://doi.org/10.1080/09540250500145072.
Coffman, K. B., & Klinowski, D. (2018). The impact of penalties for wrong answers on the gender gap in test scores. Boston: Harvard Business School.
Correll, S. J. (2004). Constraints into preferences: gender, status, and emerging career aspirations. American Sociological Review, 69(1), 93–113.
Cunha, J. M., & Miller, T. (2014). Measuring value-added in higher education: possibilities and limitations in the use of administrative data. Economics of Education Review, 42, 64–77.
Galeshi, R. (2013). Women and nontraditional fields: a comprehensive review. Journal of Sustainability Education, 4(January), 1–13.
Guiso, L., Monte, F., Sapienza, P., & Zingales, L. (2008). Culture, gender, and math. Science, 320(5880), 1164–1165.
Haemmerlie, F. M., & Montgomery, R. L. (2012). Gender differences in the academic performance and retention of undergraduate engineering majors. College Student Journal, 46(1), 40–45. Retrieved May 15, 2018 from http://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=73951015&site=ehost-live.
Hirano, K., Imbens, G. W., & Ridder, G. (2003). Efficient estimation of average treatment effects using the estimated propensity score. Econometrica, 71(4), 1161–1189. https://doi.org/10.1111/1468-0262.00442.
Huang, G., Taddese, N., & Walter, E. (2000). Entry and persistence of women and minorities in college science and engineering education. Education Statistics Quarterly, 2(3), 59–60.
Joensen, J. S., & Nielsen, H. S. (2009). Is there a causal effect of high school math on labor market outcomes? Journal of Human Resources, 44(1), 171–198.
Khandker, S. R., Koolwal, G. B., & Samad, H. A. (2010). Handbook on impact evaluation: quantitative methods and practices. Washington, D.C: World Bank Publications.
Klasen, S., & Lamanna, F. (2009). The impact of gender inequality in education and employment on economic growth: new evidence for a panel of countries. Feminist Economics, 15(3), 91–132.
Koedel, C., Mihaly, K., Rockoff, J. (2015). Value-added modeling: A review. Economics of Education Review, 47, 180–195. https://doi.org/10.1016/j.econedurev.2015.01.006.
Kokkelenberg, E. C., & Sinha, E. (2010). Who succeeds in STEM studies? An analysis of Binghamton University undergraduate students. Economics of Education Review, 29(6), 935–946. https://doi.org/10.1016/j.econedurev.2010.06.016.
MacLeod, W. B., Riehl, E., Saavedra, J. E., & Urquiola, M. (2017). The big sort: college reputation and labor market outcomes. American Economic Journal: Applied Economics, 9(3), 223–261.
Mann, A., & DiPrete, T. A. (2013). Trends in gender segregation in the choice of science and engineering majors. Social Science Research, 42(6), 1519–1541. https://doi.org/10.1016/j.ssresearch.2013.07.002.
Morales Valera, R. M., & Sifontes, D. A. (2014). Las patentes como resultado de la cooperación en I+ D en América Latina: Hechos y desafíos. Investigación & Desarrollo, 22, 1.
Niederle and Vesterlun. (2007). Do women shy away from competition? Do men compete too much? The Quarterly Journal of Economics.
OECD. (2016). Reviews of National Policies for education: Colombia. Paris: OECD Publishing. https://doi.org/10.1787/9789264250604-en.
OECD. (2017a). The pursuit of gender equality: an uphill battle. Paris: OECD Publishing. https://doi.org/10.1787/9789264281318-en.
OECD. (2017b). 2013 OECD Recommendation of the Council on Gender Equality in Education, Employment and Entrepreneurship. Paris: OECD Publishing. https://doi.org/10.1787/9789264279391-en.
Sax, L. J., Allison Kanny, M., Jacobs, J. A., Whang, H., Weintraub, D. S., & Hroch, A. (2016). Understanding the changing dynamics of the gender gap in undergraduate engineering majors: 1971-2011. Research in Higher Education, 57(5), 570–600. https://doi.org/10.1007/s11162-015-9396-5.
Schiebinger, L., Klinge, I., Sánchez de Madariaga, I., Paik, H., Schraudner, M., & Stefanick, M. (2014). Gendered innovations in science, health and medicine, engineering, and environment (pp. 2011–2013).
Schrøter, J. J., & Nielsen, H. S. (2013). Math and gender: is math a route to a high-powered career? IZA DP No. 7164. Retrieved May 10, 2018 from http://ftp.iza.org/dp7164.pdf.
Shapiro, C. A., & Sax, L. J. (2011). Major selection and persistence for women in STEM. New Directions for Institutional Research, 2011(152), 5–18.
Thévenon, O., Ali, N., Adema, W., & del Pero, A. S. (2012). Effects of reducing gender gaps in education and labour force participation on economic growth in the OECD. OECD iLibrary. https://doi.org/10.1787/5k8xb722w928-en.
Turner, S. E., & Bowen, W. G. (1999). Choice of major: the changing (inchanging) gender gap. Industrial and Labor Relations Review, 52(2), 289–313. https://doi.org/10.2307/2525167.
UNESCO. (2015). Women in science. Retrieved April 25, 2018 fromhttp://uis.unesco.org/apps/visualisations/women-in-science/.
UNESCO. (2017). Cracking the code: girls’ and women’s education in science, technology, engineering and mathematics (STEM). Retrieved April 25, 2018 from http://unesdoc.unesco.org/images/0025/002534/253479e.pdf.
van de Walle, D., & Mu, R. (2007). Fungibility and the flypaper effect of project aid: Micro-evidence for Vietnam. Journal of Development Economics, 84, 667–685. https://doi.org/10.1016/j.jdeveco.2006.12.005.
Van Langen, A., Bosker, R., & Dekkers, H. (2006). Exploring cross-national differences in gender gaps in education. Educational Research and Evaluation, 12(02), 155–177. https://doi.org/10.1080/13803610600587016.
Wang, X. (2013). Why students choose STEM majors: motivation, high school learning, and postsecondary context of support. American Educational Research Journal, 50(5), 1081–1121. https://doi.org/10.3102/0002831213488622.
Yazilitas, D., Saharso, S., de Vries, G., & Svensson, J. (2013). Gendered study choice: a literature review. A review of theory and research into the unequal representation of male and female students in mathematics, science, and technology. Educational Research and Evaluation, 19(6), 525–545. https://doi.org/10.1080/13803611.2013.803931.
Zafar, B. (2013). College major choice and the gender gap. Journal of Human Resources, 48(3), 545–595. https://doi.org/10.1353/jhr.2013.0022.
We would like to thank Hugo Ñopo (GRADE) and the seminar participants at Pontificia Universidad Javeriana for their very valuable comments and suggestions. We would also like to thank Jorge Lagos for his work as a research assistant during this project.
This research was supported by a grant from the Instituto Colombiano para la Evaluación (ICFES).
The analysis, views and opinions expressed in this article are those of the authors and do not necessarily represent those of ICFES.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
About this article
Cite this article
Gomez Soler, S.C., Abadía Alvarado, L.K. & Bernal Nisperuza, G.L. Women in STEM: does college boost their performance?. High Educ 79, 849–866 (2020). https://doi.org/10.1007/s10734-019-00441-0
- Exit exams
- Gender differences