<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>

This study was designed to investigate the correlational relationship between four school elements listed on the Texas Academic Progress Report (TAPR) and the academic achievement of 8th grade African American male students. Data for this study was provided from the Texas Education Agency's (TEA) Office for Public Information Requests. The study included four independent variables: percent of socioeconomically disadvantaged students, average years of teachers' experience, attendance rate and average class size in mathematics. The dependent variable was the 8th grade African American males' performance on the mathematics STAAR exam. The study examined scores from the mathematics STAAR exam for the years 2012-2014. The sample population included 1,540 schools and 47,169 individual test results. The results of the correlational analysis indicate that none of the independent variables were correlated to each other, but each of the independent variables had a statistically significant correlation with the dependent variable at the p < .05 level. The study also sought to explore the variance in academic achievement that could be explained by the four independent variables when used as a model. The results of the simple multiple regression suggest that not only were the results statistically significant at the p < .01 level, but the model explained 32.4% of the variance in 8th grade African American males' performance on the STAAR mathematics exam in the years 2012-2014.