NotesFAQContact Us
Collection
Advanced
Search Tips
Back to results
ERIC Number: ED575208
Record Type: Non-Journal
Publication Date: 2016
Pages: 389
Abstractor: As Provided
ISBN: 978-1-3696-4056-4
ISSN: N/A
Race, Class and Gender in Engineering Education: A Quantitative Investigation of First Year Enrollment
Phillips, Canek Moises Luna
ProQuest LLC, Ph.D. Dissertation, Purdue University
Research explanations for the disparity across both race and gender in engineering education has typically relied on a deficit model, whereby women and people of color lack the requisite knowledge or psychological characteristics that Whites and men have to become engineers in sufficient numbers. Instead of using a deficit model approach to explain gender and race disparity, in the three studies conducted for this dissertation, I approach gender and race disparity as the result of processes of segregation linked to the historic and on-going perpetuation of systemic sources of oppression in the United States. In the first study, I investigate the relationship between the odds ratios of women and men enrolled in first year US engineering programs and institutional characteristics. To do this, I employ linear regression to study data from the American Society of Engineering Education (ASEE) and the National Center for Education Statistics (NCES) to quantify relationships between odds ratios and institutional characteristics. Results of the linear regression models showed significant relationships between the cost of universities and university selectivity and the odds ratios of women choosing engineering. I theorize how the results could be related to the operation of occupational segregation in engineering, particularly how class-based markers have been historically used by women to overcome gender-based segregation in engineering.In the second study, I examine longitudinal patterns of race, gender, and intersectional combinations of race and gender in enrollments of students in first year engineering programs across the United States (US). Using enrollment data from the American Society of Engineering Education and California Post-Secondary Education Commission, I construct measures of segregation to study how trends in the disparity of students by race could be related to increases in public school segregation nationally over the past 25 years. I found that as public school segregation levels increased nationally, underrepresentation of Black and Hispanics and overrepresentation of White and Asian students has moved further toward the extremes in first year engineering programs compared to these groups' shares of high school enrollment. I conclude that the study of public school segregation and its effect on racial disparity needs greater attention, as well as that the investigation I conducted serves as a beginning towards pushing back on deficit model explanations of race and gender disparity in engineering. In the third study, I return to the investigation of odds ratios and institutional characteristics, constructing odds ratios using ASEE and NCES data based on the odds of enrollment in first year engineering programs between Asian, Black, and Hispanic students compared to White students. I again quantify the relationships between odds ratios and institutional characteristics using linear regression models and discuss results using theory based in the perspective of occupational segregation. In this case, results were inconclusive leading me to conclude that other variables that I did not consider, such as the segregation levels of schools that students come from before enrollment, should be considered as I develop my own future study into the topic. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://www.proquest.com/en-US/products/dissertations/individuals.shtml
Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: Higher Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A