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Contribution: This study examined the role of the engineering and smartness identities of three women as they made decisions about their participation in engineering majors. In addressing the under-representation of women in engineering, particularly in electrical engineering and computer science fields where they have been extremely under-represented, it is important to consider engineering identity as it has been shown to be an important component of major selection and persistence. Background: Smartness is inextricably linked to engineering and prior work has shown that identifying as smart is salient to students who choose engineering majors. However, the relative roles of students’ engineering and smartness identities as they relate to academic decision making and persistence in engineering is not well understood. Research Question: How do engineering identity and smartness identity relate to women’s decisions about choosing engineering majors in the instances of joining engineering, changing engineering major, and leaving engineering? Methodology: Data were collected from a series of three interviews with three different women. Data condensation techniques, including writing participant summary memos and analytic memos, focused on detailing participants’ academic decisions, engineering identity, and smartness identity were used for analysis. Data visualization was used to map the women’s engineering identity and smartness identity to their academic decisions related to their majors. Findings: The findings indicate the participants’ smartness identity was salient in the initial decision to matriculate into engineering, both their engineering and smartness identities remained stable as they persisted in or left engineering. And reveal complex interactions between these identities and decision making. 

Background: Those who participate in engineering are often assumed to be smart by others. At the same time, the cultural construction of what counts as “smart” is biased and therefore functions as a barrier to broadening participation in engineering. While considerable work has been done to understand engineering identity, how students understand themselves as smart is rarely made explicit in engineering identity research. Purpose: This paper is a theoretical discussion which highlights the need for engineering identity research to integrate students’ understanding of themselves as smart. By not incorporating students’ understanding of themselves as smart explicitly in work on engineering identity, we allow the bias in what gets recognized as smart to remain implicit and oppressive. Scope: In this paper, we argue that the idea of smart is very salient in engineering contexts and contributes to inequity. Then, we demonstrate how three different framings of identity allow for the explicit integration of how students are understanding themselves as smart. We also present selected examples from our empirical data to illustrate the concrete ways in which students’ understandings of themselves as smart manifest in an engineering context. Conclusions: We provided explicit opportunities for researchers to integrate students’ understandings of themselves as smart across three different framings of identity and how such understanding has shown up in our empirical research. In doing so, we conclude that making “smart” explicit in engineering identity provides a way to understand the exclusionary nature of engineering, and a new lens to apply when considering efforts to broaden participation in engineering. 

A well-developed interview protocol is an essential data collection tool in qualitative research. An established process to refine interview protocols can help build quality and consistency into data collection. However, despite the importance placed on interview protocols by academic texts, there is little guidance regarding how to systematically develop and refine interview protocols, particularly when exploring complex constructs, such as beliefs and identity. In this special session, attendees will learn and practice an approach for refining interview protocols for investigating complex constructs in engineering education. We share this interview refinement approach as it enabled us to determine if our interview questions prompted participants to provide data essential to answering our research questions for a pilot study investigating students' beliefs and identities. This special session will also include conversations around best practices related to data collection to access complex constructs and how these practices can impact and shape future research. We welcome attendees of all experience levels (novice to expert) with regard to designing interview protocols. The session will be facilitated by Dr. Emily Dringenberg, Dr. Rachel Kajfez, and their graduate students. Dr. Dringenberg is a qualitative researcher well versed in beliefs. Dr. Kajfez is a mixed methods researcher well versed in identity. Both have multiple NSF grants exploring these complex constructs.