Thesis advisor: Michael Russell / Intersectionality theory garners increased attention from researchers interested in understanding the many ways in which oppression impacts lived experiences. In any given present and evolving context, oppression leads to advantages for some social positions and disadvantages for others (Collins & Bilge, 2016; Crenshaw, 1989). Quantitative researchers have attempted to adapt statistical modeling methods to reflect intersectional identities as a proxy for oppression and advantage in their models (Bauer et al., 2021; Schudde, 2018). This dissertation expanded on existing knowledge about the statistical limitations of three methods of modeling intersectional analyses on a continuous outcome variable: 1) Interaction, 2) Categorical, and 3) MAIDHA (multilevel analysis of individual heterogeneity and individual accuracy). Using a Monte Carlo simulation, four demographic data characteristics were manipulated to explore the three models under different scenarios which manipulated: a) the number of demographic categories (and thus intersections); b) the proportion of the sample represented by each demographic group; c) the within-intersectional-group variance in the outcome variable of interest; d) overall sample size. Each scenario and model were replicated 1000 times; results summarized performance of the intersection estimates and effect detection using the outcomes: bias, accuracy, power, type 1 error, and confidence interval coverage. The fundamental questions that guided this dissertation were: 1. What are the statistical advantages and disadvantages of each model under different demographic data characteristics? 2. In what ways does each model perform differently from one another under each demographic data characteristic condition? The findings of this dissertation contribute to intersectional quantitative research methods by providing greater insight into how each model performs under more complex data scenarios. / Thesis (PhD) — Boston College, 2024. / Submitted to: Boston College. Lynch School of Education. / Discipline: Measurement, Evaluation, Statistics & Assessment.

This dissertation explores the potential for higher education to promote the development of critical being among diverse students, including three studies that employ critical quantitative approaches. The first chapter proposes critical being as an alternative to critical thinking that better reflects the purposes of higher education for the public good. In Chapter Two, I create a survey-based instrument measuring critical being, including three factors that are theoretically grounded in the work of Barnett (1997) and Davies (2015). Chapter Three examines the relationship between specific instructional practices associated with academic challenge and four-year growth in critical being among three racial and/or ethnic groups traditionally underrepresented in higher education: Black and African American students, Asian and Pacific Islander students, and Hispanic, Latinx and Chicano students. Chapter Four focuses on college instructors, exploring the relationship of individual, academic, and organizational factors with instructors’ emphasis of critical being in the classroom and their beliefs about students’ abilities and efforts. Finally, Chapter Five returns to the necessity for higher education to center critical being in order to equip students to be well-informed agents of social change. By bringing together the results of the three studies, this chapter also considers the implications of higher education for critical being, offers self-reflection on the implementation of critical quantitative approaches, and looks forward in making recommendations for future research.

This three-manuscript formatted dissertation interrogated the effectiveness of high-impact educational practices for marginalized students through the use of critical quantitative inquiry. The first empirical manuscript used data from the Wabash National Study of Liberal Arts education to explore the role of race and class on students’ engagement in and effects from high-impact practices. Findings from this manuscript suggest significant differences in academic motivation change over the first year of college when race and class were examined together, while no differences when just class was examined. The second empirical manuscript used data from the National Study of LGBTQ Student Success to examine the intersections of environment and participation in and effect from high-impact practices for lesbian, gay, bisexual, and queer (LGBQ+) students. Findings from this manuscript suggested that students’ perceptions of overall support and their relations with instructors mediated the influence that participation in high-impact practices had on students’ academic development. Finally, the third main manuscript considered the utility of critical quantitative inquiry and ways researchers can combine critical theory into quantitative research.

<p>Socioeconomic inequality unduly impacts the pathways of socioeconomically disadvantaged students (SDS) in engineering. Past and present scholarship suggests that inequitable access to physical and interpersonal resources inhibits K-16+ students' ability to engage in Science, Technology, Engineering, and Mathematics (STEM) meaningfully. This lack of access negatively impacts SDS' pursuit of, and success in, engineering. Thus far, quantitative studies seeking to understand SDS' trajectories to and through engineering have used income as a proxy for socioeconomic disadvantage. However, such measures are not theoretically positioned to accurately depict or account for the complex sociological processes that lead to, or result from, socioeconomic inequality. Furthermore, such measures do not account for parallel inequalities such as racism, sexism, and classism that exist, influence, and are influenced by it. Therefore, the purpose of this work was to 1) develop a more sociologically accurate measure of socioeconomic inequality, 2) to use that measure to identify the impacts of such inequality on SDS' pathways to and through engineering, and finally, 3) to explore the narrative experiences of SDS when accounting for a more accurate depiction. Using a Critical Realist Feminist approach to structural equation modeling, restricted data from the National Center for Education Statistics’ Educational Longitudinal Study of 2002 (ELS:2002) as well as other supplemental data were used to construct and test a more complex and representative measure of socioeconomic disadvantage, the Model of Socioeconomic Inequality (Study 1). Study 2 used this model to examine how aspects predicting important engineering student outcomes. Neighborhood location and conditions, level of Parent Educational Involvement, and availability of Household Educational Resources negatively impact SDS' opportunities to engage and succeed in engineering and college more broadly. Furthermore, the model suggested that such interactions are uniquely mediated by the intersectional inequalities experienced by SDS and their families. Finally, a rich narrative of one student, Samantha, is included to better understand the lived experiences of SDS amongst their pathways to and through engineering. Samantha was a Queer Asian American female SDS graduating from Computer Science Engineering who has low scores on Parent Educational Involvement and Household Educational Resources. Samantha's narrative shows the important role that the factors identified in the Model of Socioeconomic Inequality had in her experiences. Specifically, Samantha had little access to Parent Educational Involvement and Household Educational Resources from her parents. Rather, these forms of support came from what she referred to as her ``chosen family,'' a group of professors, co-workers, friends, and others who viewed and supported her identity authentically and provided her physical resources when she needed them. Access to this group and the resources they provided supported Samantha's belonging and her ability to succeed in engineering. However, Samantha's narrative also uncovered findings not included in the Model of Socioeconomic Inequality. Specifically, Samantha's narrative suggested she had experienced significant, long-term traumas that were both related and unrelated to her socioeconomic experiences. These traumas negatively impacted Samantha's feelings of belonging and caused her to question her place in engineering, but they were partially mitigated by the support of her chosen family. This three-study dissertation challenges current engineering education thinking regarding the knowledge and study of socioeconomics, trauma, and Intersectionality more broadly. It also challenges engineering education researchers and practitioners to question the current methods of how they support SDS in a multitude of spaces.</p>

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