Abstract:

International literature documents persistent gender differences in both academic achievement and educational choices, with long-term implications for female participation in STEM (science, technology, engineering, mathematics) fields (Breda & Napp, 2019; OECD, 2023; Reardon et al., 2019). However, empirical evidence on the role of the relative achievement gap (i.e., the comparative difference between females and males) in driving gendered self-selection during critical educational transitions remains limited.

This study uses standardized learning assessment data collected by INVALSI to construct a pseudo-longitudinal dataset linking student performance in primary and lower secondary school to subsequent enrollment choices in upper secondary education.

Results show that, conditional on absolute achievement, an increase in the mathematics performance gap to the disadvantage of female students is associated with a lower likelihood of choosing science-oriented upper secondary schools. The relative differential emerges as a robust predictor of choice, suggesting that comparative competence signals – rather than absolute learning levels – guide decision-making processes during school tracking. These findings are consistent with models of aspiration formation and academic identity that emphasize the role of relative performance and social comparison mechanisms (Buser et al., 2014; Correll, 2001; Murphy & Weinhardt, 2020).

Further analyses (Authir, under review) show a similar pattern in the transition from upper secondary school to university: even in the selection of STEM degree programs, the gender achievement gap is a more relevant predictor than absolute performance levels. Overall, the results suggest that comparative learning differentials act as a cumulative self-selection mechanism, contributing to the persistence of gender segregation in scientific pathways throughout the educational cycle.

References:
[1] Buser, T., Niederle, M., & Oosterbeek, H. (2014). Gender, competitiveness, and career choices. Quarterly Journal of Economics, 129(3), 1409–1447. https://doi.org/10.1093/qje/qju009
[2] Contini, D., Di Tommaso, M. L., Maccagnan, A., & Mendolia, S. (2023). Gender differences in high school choices: Do math and language skills play a role? IZA Discussion Paper No. 16584.
[3] Correll, S. J. (2001). Gender and the career choice process: The role of biased self-assessments. American Journal of Sociology, 106(6), 1691–1730. https://doi.org/10.1086/321299
[4] Murphy, R., & Weinhardt, F. (2020). Top of the class: The importance of ordinal rank. Review of Economic Studies, 87(6), 2777–2826. https://doi.org/10.1093/restud/rdaa020
[5] OECD. (2023). Education at a Glance 2023: OECD Indicators. OECD Publishing. https://doi.org/10.1787/e13bef63-en
[6] OECD. (2023). The gender gap in education: Outcomes, attitudes and aspirations. OECD Publishing.
[7] Reardon, S. F., Kalogrides, D., & Shores, K. (2019). The geography of racial/ethnic test score gaps. American Journal of Sociology, 124(4), 1164–1221. https://doi.org/10.1086/700678
[8] Author, A., [Co-authors]. (forthcoming). Bridging the gender gap in mathematics: examining STEM enrolment rate by gender in Higher Education, in Italian Provinces. Manuscript under review.

Keywords:

Gender gap, relative performance, school tracking, educational transitions.