A Combined Model for Predicting Engineering Identity in Undergraduate Students

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 standalone 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. Introduction Engineering is a diverse discipline demanding skill and competency in such areas as math and applied sciences (e.g., applied physics). The interdisciplinary nature of engineering calls into question the extent to which those participating in the community of practice—students as well as professionals—see themselves as engineers. The lack of alignment of one’s personal identity and the identity of an engineer may cause some to feel as if they do not belong. It is well documented that engineering disciplines have low female and minority representation (Chemers, Zurbriggen, Syed, Goza, & Bearman, 2011; Chubin, May, & Babco, 2005; Faulkner, 2009; Hill, Corbett, & St Rose, 2010). Though men and women leave engineering at similar rates, women have been found to leave at an earlier stage than men (Godwin & Potvin, 2015; Min, Zhang, Long, Anderson, & Ohland, 2011) and less than a quarter of all engineering degrees are awarded to women (Ohland et al., 2008). Similarly, underrepresented racial and ethnic minorities represent fewer than 20% of engineering student populations in the United States (Chubin et al., 2005). Perhaps some of this representation is due to the lack of these groups identifying with the field of engineering, as suggested by Tonso (2014) in her review of engineering identity. Identity as a construct has been defined and measured in various ways across a diverse body of literature (Patrick & Borrego, 2016). Such definitions include an integration of multiple identities such as social, personal and academic (Chemers et al., 2011); “being recognized as a ‘certain type’ of person” (Gee, 2000); how students see themselves with respect to a content area, based on their perceptions and navigation of everyday experiences in that area (Cribbs, Cass, Hazari, Sadler, & Sonnert, 2016); and a composite of students’ performance, competence, and recognition in a domain (Carlone & Johnson, 2007). The last definition is the focus of this current study. This composite definition emerged from Carlone and Johnson’s (2007) qualitative study on science identity as the triangulation of performance, competence, and recognition in science. Performance describes a student’s belief in their ability to perform in their classes or to conduct tasks. Similarly, competence describes a student’s belief in their ability to understand content. Performance and competence are closely linked. In later quantitative studies of identity, these factors were combined into one performance/competence factor, thus reflecting student’s self-perception of performance as linked to their actual performance. Recognition describes how parents, relatives, friends, and instructors see the student in a given context. This framework was expanded by Hazari, Sonnert, Sadler, and Shanahan (2010) in their quantitative analysis of physics identity with the addition of interest to the framework. Interest describes one’s enjoyment in learning or interest in learning about engineering. The PCIR framework refers to the performance/competence, interest, and recognition framework, collectively throughout this paper. Despite the expanding use of this PCIR framework, few studies treat engineering identity as an outcome variable. As the popularity of studying identity in engineering builds, we can point to several other studies that have employed the PCIR framework to study math identity, science identity, and physics identity (Cass, Hazari, Cribbs, Sadler, & Sonnert, 2011; Cribbs et al., 2016; Cribbs, Hazari, Sonnert, & Sadler, 2015; Godwin, Potvin, & Hazari, 2013; Godwin, Potvin, Hazari, & Lock, 2013). Quantitative work largely treats the identity construct as a stepping stone to examine STEM career interest (Kier, Blanchard, Osborne, & Albert, 2014) or choice of engineering career (Cribbs et al., 2016; Godwin, Potvin, Hazari, et al., 2013; Lent et al., 2008; Sheppard, Antonio, Brunhaver, & Gilmartin, 2014; Sheppard et al., 2010) in high school or first-year undergraduate students. In this study, we focus on students in their first year and beyond to add to the body of literature on engineering undergraduates (Godwin, 2016; Godwin, Potvin, Hazari, & Lock, 2016). Specifically, the aim of this study is to simultaneously explore the PCIR framework in the context of math, physics, and engineering and examine the effects on engineering identity in undergraduate engineering students across their trajectory to matriculation.