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Research Context and Methodology

The findings presented in this chapter stem from a larger, NSF-funded ethnographic study of Latinx students’ experiences in senior-level capstone ME/CS courses and entry into the profession. The study took place at a large, public, research-intensive HSI located on the US—Mexico border. At the time of this study, university enrollment included more than 25,000 students, 80.2% of whom were Hispanic/Latinx, an additional 4.1% being Mexican nationals. Of this student body, 73% were Pell eligible, and 50.9% were first-generation college students.

Given the focus on students’ experiences within the social context of ME/CS, our chosen methodological approach for the larger study was ethnographic in orientation. Ethnography, which involves a combination of observational, descriptive, and interpretive methods (Hammersley & Atkinson, 2007), is used in a variety of disciplines as a way to investigate complex sociocultural phenomena with the understanding that the human experience is irreducible. For the purposes of this chapter, we employ a case study methodology (Yin, 2018) in order to illuminate the experiences, and patterns across experiences, of four focal participants: two Latina Mechanical

Engineering graduates, and two Latina Computer Science graduates. In constructing these case studies out of our larger body of data, we relied on three primary ethnographic data sources: (1) participant observation and field notes; (2) in-depth interviews; and (3) artifacts. These data, along with video recordings and questionnaires, were collected over the course of two academic years as part of our larger study.

The larger study focused on 27 students enrolled in senior capstone courses in ME/CS: 17 men and 10 women. The research team, which was comprised of two education faculty and two doctoral students in education (three out of four researchers identified as Mexican or Latinx), followed six teams of students enrolled in ME/CS senior capstone courses. Each semester, researchers on our team conducted more than 30 hours of participant observation in senior-level ME/CS capstone courses—one semester for ME and a two-semester sequence in CS—with students on selected focal teams. Those focal students then participated in a series of three in-depth interviews, which were conducted using the Seidman (2013) three-part interview method. The first two interviews took place one week apart at the end of the first semester or year of participant observation, while the third and final interview took place within 8—12 months after graduation, to learn more about students’ experiences moving into the profession (or not). Interviews were conducted in both Spanish and English, depending on the preference of the participant. Finally, the research team collected artifacts, including course syllabi and course projects, to gain a more comprehensive understanding of the context of the senior capstone courses and course projects.

Data analysis of the interviews and field notes was an iterative process, involving multiple stages. The focus of our analysis was the factors that shaped our participants’ experiences of persistence in engineering—particularly for our Latina participants. We focused primarily on the interview data for the first two in-depth interviews, which were cross-checked with the participant observation and artifact data. All interviews were coded in NVivo using an “open coding” and “focused coding” approach (Emerson, Fretz, & Shaw, 2011). Once initial themes were established, we returned to the theoretical literature, where the concept of identities (Gee, 1989) and social capital/social resources (Lin, 1999) gained particular relevance in relation to what we found in the initial round of coding.

With identity and social capital as a frame, we initiated a second round of more focused coding, and focused on four of the ten participants. These participants were selected based on the representativeness of both their experiences and their fields (two in mechanical engineering and two in computer science). In our subsequent rounds of coding, we focused on the social resources identified by participants, which in turn shaped the development of each participant’s case. In the case studies presented, we attempt to provide a holistic representation of each participant’s experience based on their own narratives and our participant observation. In the next section, we present each of the four cases. We start with Alicia and Daena, two Mechanical Engineering students, and then present the cases of Alejandra and Andrea, both in Computer Science (all names are pseudonyms).

Case Studies: Latinas in Mechanical Engineering and Computer Science

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