The impact of gender roles and previous exposure on major choice, perceived competence, and belonging: a qualitative study of students in computer science and bioinformatics classes

ABSTRACT

Background and Context

While biology has strong female representation, computer science is the least gender equitable of the STEM fields. A better understanding of the barriers that keep women out of computational fields will help overcome those barriers to create a more diverse workforce.

Objective

We investigated the complexities that influence students’ major choice and their sense of belonging. We were particularly interested in students adjacent to computer science and differences by gender.

Method

We conducted semi-structured interviews of nineteen students from computer science or bioinformatics courses. We used inductive thematic analysis that included iterative readings of interview transcripts, line-by-line coding, and final theme selection.

Findings

Most students described pressures stemming from traditional gender roles as they chose their major, but specific pressures differed by gender. Men were more likely to report early exposure to their major field, and women noted feeling behind without those early experiences. This hurt the women’s sense of belonging, as did having few female peers.

Implications

Increasing early exposure to coding may increase women's representation and sense of belonging in computational fields. Women from contexts with emphasis on traditional gender roles may be drawn to computational fields if they see opportunities for flexible positions.

KEYWORDS:

• Women
• female
• career development
• quantitative biology
• social cognitive career theory
• conservative religious populations

Acknowledgments

We would like to acknowledge Anika Hubbard for organizing interview transcripts prior to analysis and Jack Stalnaker and Kevin Gutierrez for sharing thoughts on the interviews after an initial listen.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/08993408.2022.2160144

Additional information

Funding

This work was supported by Brigham Young University through a College Undergraduate Research Award given to undergraduate students Emilee Severe and Anika Hubbard.