BACKGROUNDConcern for workforce needs, social justice, and the diversification of the engineering profession make it critical to understand how different metrics may overestimate or underestimate the success of various race-gender populations in engineering. PURPOSE (HYPOTHESIS)While earlier work found that women in nearly all racial groups persist to the eighth semester at rates comparable to men, results vary in studies that use other measures of success, providing an incentive to compare multiple measures of success in the same population. DESIGN/METHODThe eight-semester persistence and six-year graduation rates are compared for various race-gender populations using a longitudinal, comprehensive dataset of more than 75,000 students matriculating in engineering at nine universities from 1988-1998. RESULTSGender differences in persistence of Asian, Black, Hispanic, Native American, and White students are far outweighed by institutional differences. Racial differences are more pronounced, however, revealing some patterns that transcend institutional differences. CONCLUSIONSOur work demonstrates that trajectories of persistence are non-linear, gendered, and racialized, and further that higher education has developed the way in which persistence is studied based on the behavior of the majority, specifically the White, male population. Even if institutions were to treat all students equally, the outcomes will not necessarily be the same because various populations respond differently to the same conditions. Using eight-semester persistence may result in a "systematic majority measurement bias." Therefore, multiple measures may be needed to describe outcomes in diverse populations.
Background: Pipeline and pathways models influence persistence metrics used to study how students navigate engineering education. Purpose: This study presents pipeline, pathways, and ecosystem models and their associated metrics, compares and contrasts these models using an intersectional approach to explore persistence, and advocates for use of an ecosystem model. Design/Method: This study presents a quantitative perspective of engineering student outcomes disaggregated by discipline, race/ethnicity, and sex. It includes 111,925 engineering students from 11 U.S. universities, including first-time-incollege and transfer students who ever majored in the most common engineering disciplines: chemical, civil, electrical, industrial, and mechanical engineering. Contemporary data visualization methods are used to display quantitative data and clarify their complexity. Results: This work captures the intersectionality of race/ethnicity, sex, and discipline with metrics that are new or little used, such as stickiness (retention by a discipline), migrator graduation rate, and migration yield (attraction of a discipline). Using these metrics, we uncover information about the success of students who migrate between and among the top five engineering disciplines. Conclusions: Stickiness, migrator graduation rates, and migration yield metrics coupled with contemporary data visualization methods provide insights into the student experience not afforded by the conventional pipeline and pathways models.Considering engineering education as an ecosystem tells stories of complexity and nuance, opening possibilities for new research. K E Y W O R D S ecosystem, engineering pathways, engineering pipeline, retention, underrepresentation
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