Prior to college, many students do not have experience with engineering, but some ultimately choose an engineering career. Additionally, women choose engineering at lower rates than men, which results in women’s underrepresentation. The framework of critical engineering agency (CEA) is utilized to understand student attitudes and beliefs for choosing engineering. We investigate the relationships among students’ math and physics identities in high school that predict choice of engineering careers; how students’ beliefs about science and technology predict a choice of engineering careers; whether these beliefs are different by gender; and how well CEA explains students’ engineering choice. The data were drawn from the nationally representative Sustainability and Gender in Engineering (SaGE) survey distributed during Fall 2011 (n = 6,772). Structural equation modeling (SEM) was used to understand students’ affective beliefs for predicting engineering choice in college. Multiple subject-related identities compose engineering students’ identity at the beginning of college. Recognition from others and interest in a subject are important predictors of developing an identity. Students’ performance/competence alone are not significant predictors of engineering, but are mediated by interest and recognition from others. Student identities and agency beliefs are significant predictors of engineering choice (explaining 20.2% of the variance). Gender differences were found for students’ math and physics identities and agency beliefs. Students’ self-beliefs account for approximately one-fifth of the variance in engineering choice in the transition from high school to college. Steps can be taken to improve students’ affective beliefs in early engineering experiences through addressing identity and agency beliefs.
critical engineering agency, engineering choice, structural equation modeling
Date of this Version
Godwin, A., Potvin, G., Hazari, Z., & Lock, R. (2016). Identity, Critical Agency, and Engineering: An Affective Model for Predicting Engineering as a Career Choice 105(2), 312–340. doi: 10.1002/jee.20118