Document Type
Conference Proceeding
Publication Date
4-2025
Abstract
This study examines the intersectional factors influencing early mathematics identity development among underrepresented secondary students (grades 9-10) with aspirations in engineering. Mathematics identity is a well-established predictor of long-term persistence in engineering, making its early formation critical to understanding student retention in the engineering pipeline. Grounded in Bronfenbrenner's bioecological framework, this study situates learning within nested layers of influence. Using data form the nationally representative High School Longitudinal Study of 2009 (HSLS:09), which includes over 23,000 9th-graders, a hierarchical multiple regression analysis was conducted. The analysis examined intersections of race and gender identity across 16 variables spanning individual, micro-, meso-, and exosystem factors, controlling for 8th-grade mathematics scores. Results revealed that the model explained 58.8% of the variance in mathematics identity (F[24],[176]=121.11,p< .001). Developing a community of practice - characterized by having a math or science mentor and participating in a school math club - emerged as a key mesosystemic predictor (beta=.371, p=.004) of 9th-grade math identity (beta=.367, pÁ.001) and current math interest (beta=.377,p< .001) among engineering-aspiring students. These findings highlight the critical role of mesosystemic support in fostering early mathematics identity and provide a robust predictive framework for broadening participation of underrepresented students in engineering pathways. Implications for educators, policymakers, and curriculum designers include fostering inclusive communities of practice and enhancing support systems to promote equitable engineering opportunities.
Recommended Citation
D. D. Havard and A. Quirós-Arauz, "Intersectional Predictors of Early Mathematics Identity Among Underrepresented Engineering-interested Students," 2025 IEEE Global Engineering Education Conference (EDUCON), London, United Kingdom, 2025, pp. 1-10, https://doi.org/10.1109/EDUCON62633.2025.11016429
Peer Reviewed
1
Copyright
© 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Included in
Data Science Commons, Engineering Education Commons, Science and Mathematics Education Commons, Secondary Education Commons
Comments
This is a pre-copy-editing, author-produced PDF of an article accepted for publication in 2025 IEEE Global Engineering Education Conference (EDUCON). This article may not exactly replicate the final published version. The definitive publisher-authenticated version is available online at https://doi.org/10.1109/EDUCON62633.2025.11016429.