A Combined Model for Predicting Engineering Identity in Undergraduate Students

Abstract Several recent studies have focused on measures of student attitudes and beliefs to predict outcomes such as career choice, integration, persistence, and identity in engineering. The body of research on identity in engineering education has converged around a framework based on three factors: performance/competence (i.e., ability or beliefs that one can perform well or understands concepts), interest in the subject matter, and recognition by others (i.e., peers, family members, teachers) as the type of person who can understand/complete the subject matter. Prior studies have shown math and physics identity factors to be predictive of engineering major choice in first-year undergraduates. However, these studies have not included engineering identity factors. The first aim of this paper is to test a combined model for predicting engineering identity. The combined model includes previously established factors of math and physics identity and newly established engineering factors of the same kind. The second aim is to compare this combined model to a model using only engineering factors to investigate the usefulness of these factors as stand-alone predictors of engineering identity. The study draws on data collected from 1202 undergraduate engineering students in three majors across two public institutions in the southwestern United States. Using linear regression, the results show that all three domains (math, physics, and engineering) individually account for a significant proportion of the variance in engineering identity after controlling for student demographic variables. The combined model explained a total of 29.1% of the variance in engineering identity. Of the non-engineering factors, only math performance/competence was a significant predictor. However, all three engineering factors were significant predictors in that model. Comparatively, the stand-alone model using just the engineering factors explained nearly the same proportion of variance in engineering identity as the combined model, 28.9%. These findings indicate that while students’ math and physics beliefs are important to predicting engineering identity, their engineering beliefs provide equivalent explanatory power. Future research would be better informed through an understanding of how these three domain areas contribute to our understanding of identity and other outcomes.