Factors Influencing Retention of Transgender and Gender Nonconforming Students in Undergraduate STEM Majors

Maloy, Jeffrey; Kwapisz, Monika B.; Hughes, Bryce E.

doi:10.1187/cbe.21-05-0136

Cited by 54 publications

(54 citation statements)

References 49 publications

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“…Existing research is mixed on how well the gender parity for men and women in a STEM field predicts the presence of queer-spectrum individuals, and thus the patterns of under-representation in our data may be a systemic STEM-wide problem and may follow different patterns than the patterns of under-representation of women [ 1 , 5 , 20 ]. Yoder and Mathesis [ 26 ] found that the percentage of women in a field was correlated with the likelihood that lesbian, gay, or bisexual individuals disclosed their queer identity to colleagues, which is different from predicting overall numbers of LGB individuals, but does provide some information about climate.…”

Section: Discussionmentioning

confidence: 99%

“…Sansone and Carpenter [ 32 ] found a higher number of men in same-sex couples in STEM fields that have higher proportions of women. But, conversely, Malory and Hughes [ 5 ] found the lowest representation of trans and non-binary students in biology classes, and Cech And Waidzunas (2021) found no relationship between representation of queer-spectrum individuals and STEM field. Therefore, it would be erroneous to assume that underrepresentation is a problem limited to engineering and computer science or that the under-representation of queer-spectrum individuals inherently parallels the underrepresentation of women in STEM.…”

Section: Discussionmentioning

confidence: 99%

“…Specifically, queer-spectrum STEM professionals and students experience exclusion from networking and resources, harassment, devaluating of their contributions, a more negative work environment, decreased professional success, and a chilly climate towards any discussion of their identity, as queer identities are often seen as irrelevant and not to be discussed [ 1 – 3 , 8 – 13 ]. The consequences of this chilly climate include queer-spectrum students’ under-representation and lower persistence than their cisgender and heterosexual peers, and the higher likelihood of queer-spectrum STEM professionals to consider and create plans to leave not only their profession, but STEM completely [ 1 , 7 , 14 – 16 ]. Demographic collection practices often exacerbate this chilly climate, as surveys often have limited gender options and rarely ask questions relating to sexual, romantic, and related orientations [ 1 , 17 – 20 ], limiting research on the experiences of queer-spectrum people [ 21 – 24 ].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Data collection is a key step toward understanding successes and failures of educating and supporting queer-spectrum people in STEM [ 7 , 16 , 28 ]. The importance of collecting data on the experiences of queer-spectrum people is exemplified by how participation in undergraduate research experiences, a strong predictor of STEM retention overall, does not predict the persistence of queer-spectrum students [ 16 , 29 ], as well as the widespread inequities for queer-spectrum STEM professionals revealed in Cech and Waidzunas’ recently published large-scale survey data [ 1 ]. However, even in surveys that create space for queer-spectrum identities, there is no consensus on best practices, leading to a range of data collection practices that may or may not accurately capture individuals’ identities and that yield data that are not necessarily comparable [ 21 – 24 , 28 , 30 , 31 ].…”

Section: Introductionmentioning

confidence: 99%

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Revealing the queer-spectrum in STEM through robust demographic data collection in undergraduate engineering and computer science courses at four institutions

2022

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Queer identities are often ignored in diversity initiatives, yet there is a growing body of research that describes notable heterosexist and gender-normative expectations in STEM that lead to unsupportive and discriminatory environments and to the lower persistence of queer individuals. Research on the experiences of queer-spectrum individuals is limited by current demographic practices. In surveys that are queer-inclusive there is no consensus on best practices, and individuals with queer genders and queer sexual, romantic, and related orientations are often lumped together in a general category (e.g. LGBTQ+). We developed two queer-inclusive demographics questions and administered them as part of a larger study in undergraduate engineering and computer science classes (n = 3698), to determine which of three survey types for gender (conventional, queered, open-ended) provided the most robust data and compared responses to national data to determine if students with queer genders and/or queer sexual, romantic, and related orientations were underrepresented in engineering and computer science programs. The gender survey with queer-identity options provided the most robust data, as measured by higher response rates and relatively high rates of disclosing queer identities. The conventional survey (male, female, other) had significantly fewer students disclose queer identities, and the open-ended survey had a significantly higher non-response rate. Allowing for multiple responses on the survey was important: 78% of those with queer gender identities and 9% of those with queer sexual, romantic and related orientations selected multiple identities within the same survey question. Queer students in our study were underrepresented relative to national data. Students who disclosed queer gender identities were 7/100ths of the expected number, and those with queer orientations were under-represented by one-quarter. Further work developing a research-based queered demographics instrument is needed for larger-scale changes in demographics practices, which will help others identify and address barriers that queer-spectrum individuals face in STEM.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%