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The Minority in The Minority, Black Women in Computer Science Fields: A Phenomenological Study

by Blanche' D Anderson

Institution: Liberty University
Department:
Degree:
Year: 2022
Keywords: Black women; STEM; STEAM; intersectionality; social learning theory of career decision-making; computer engineering; computer science; cybersecurity; data science; information systems; information technology; software engineering; Computer Sciences; Highe
Posted: 3/25/2025
Record ID: 2262020
Full text PDF: https://digitalcommons.liberty.edu/doctoral/3928 https://digitalcommons.liberty.edu/context/doctoral/article/4987/viewcontent/1_Anderson_2C_20Blanche_20_28L27077293_29.pdf


Abstract

The purpose of this transcendental phenomenological study was to describe the lived experiences of Black women with a bachelor’s, master’s, or doctoral degree in computer science, currently employed in the United States. The theory guiding this study was Krumboltz’s social learning theory of career decision-making, as it provides a foundation for understanding how a combination of factors leads to an individual’s educational and occupational preferences and skills. This qualitative study answered the following central research question: What are the lived experiences of Black women with a bachelor’s, master’s, or doctoral degree in computer science, currently employed in the United States? Purposeful criterion sampling was used to select between 12 to 15 participants from the Society of Women Engineers who met the following criteria: a female, Black or African American, with a bachelor’s, master’s, or doctoral degree in computer science, graduated from an accredited college, university, or vocational program, and currently employed in the United States. Data collection methods included individual interviews, letter writing, and focus groups. Data analysis followed Moustakas modified approach: setting aside personal experiences and prejudgments, organizing data and conducting horizonalization, developing clusters of meaning into common themes, generating and combining textural and structural descriptions, and generating a composite description of the phenomenon experienced by all participants.

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