Beyond Pipeline and Pathways: Ecosystem Metrics

Autor/inn/en	Lord, Susan M.; Ohland, Matthew W.; Layton, Richard A.; Camacho, Michelle M.
Titel	Beyond Pipeline and Pathways: Ecosystem Metrics
Quelle	In: Journal of Engineering Education, 108 (2019) 1, S.32-56 (25 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1069-4730
DOI	10.1002/jee.20250
Schlagwörter	College Students; Engineering Education; Majors (Students); Ecology; Disproportionate Representation; Race; Ethnicity; Sex; School Holding Power; Academic Achievement; Outcomes of Education; Graduation Rate + Suchen Sie Ihr Suchwort? Collegestudent; Ingenieurausbildung; Ökologie; Rasse; Abstammung; Ethnizität; Geschlecht; Geschlechtsverkehr; Schulleistung; Lernleistung; Schulerfolg
Abstract	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-in-college 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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01