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Recent data reveal that a higher percentage of Black women (9.7%) are enrolled in college than any other group, topping Asian women (8.7%), White women (7.1%) and White men (6.1%). Despite these gains in college attendance, Black women are often underrepresented in the fields of engineering and computer science. This paper presents the findings from a qualitative study that investigated the identity and experiences of Black women who are pursuing doctoral degrees in engineering and computer science. This research is grounded on the tenet that one cannot effectively serve or impact a community until he/she genuinely understands the issues and challenges facing the people who are its members. This work explores how Black female doctoral students persist in environments where they are grossly underrepresented. Content analysis is used to examine interview data obtained from 13 Black women who are pursing doctoral degrees in engineering and computer science. This paper concludes with some of the key challenges these women face in their programs on a daily basis. The goal of this research is to bring awareness to not only the challenges, but also potential strategies to increase the retention and persistence of Black women in engineering and computer science across all academic levels.
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Without Role Models: A Few Pioneering Women Engineers in Asia
The importance of role models in inspiring and influencing the career paths of young people cannot be overstated, particularly in the fields where certain population segments are under-represented. However, when there are no role models, a few exceptional people become pioneers; these are people who carve out their own paths. Most research in early history of women in engineering focuses on the Western world, with relatively little information from the other parts of the globe. This paper presents the stories of a few Asian women who went against the odds, against social norms and expectations, without role models, and ventured into the field of engineering.
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- Award ID(s):
- 1937849
- PAR ID:
- 10327664
- Date Published:
- Journal Name:
- American Behavioral Scientist
- ISSN:
- 0002-7642
- Page Range / eLocation ID:
- 000276422210785
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1177/00027642221078508
