New Orleans, Louisiana
February 20, 2022
February 20, 2022
July 20, 2022
Diversity and CoNECD Paper Sessions
Keywords Undergraduate, Gender, Engineering, Computer Science
Introduction Despite efforts to diversify undergraduate science, technology, engineering, and mathematics (STEM) programs, there is still a gender gap in many (male-dominated) STEM fields. That is, regardless of precollegiate academic abilities, women are underrepresented in fields such as engineering and computer science (NGC, 2020; Schneider et al., 2015) and often experience more gender harassment in these fields when compared to their female counterparts in gender-equivalent fields (i.e. Natural Sciences; Brooke et al., 2017). Research indicates that exposure to persistent gender stereotypes, often reinforced by numerical dominance, lowers women’s sense of belonging and hinders personal-professional identity development, which in turn leads to women leaving STEM fields at a higher rate than their male peers (Dasgupta & Stout, 2014; Diekman et al., 2010). Balanced identity theory (Greenwald et al., 1998), suggests that individuals who achieve balance across central personal-professional identities will be more likely persist in their academic and career pursuits. This study utilizes a novel methodology of individual Balanced Identity Design (BID; NSF #1920786), which can be used to quantify the extent to which these identities are in balance or in conflict.
Current Study In the present study, the three most relevant central personal-professional identities were: Self-STEM, Self-Gender, and the STEM-Gender association. These three central identities can be measured explicitly (i.e. survey scales) and implicitly (i.e. Implicit Association Tests; Greenwald et al., 2002). The present study sought to understand if identity balance varied as a function of gender identity (men, women) and major (Science, Engineering/Computer Science).
Methods The current study is a part of a larger, 2.5-year longitudinal study of identity development and balance among ethnically diverse undergraduates in STEM majors within Natural Sciences (73%), Engineering (18%), and Computer Science (9%) from three California State University schools. The analytic sample (measured Fall 2018) included 146 juniors and seniors (59% Hispanic, 58% female). Potential participants were emailed an initial screening survey to verify that they were currently of junior/senior academic status, either White or Hispanic/Latinx, and currently enrolled in a STEM field. Following acceptance into the MyCollegePathways study, eligible participants completed a series of three randomly displayed, online Implicit Association Tests (IAT; Greenwald et al., 1998), and answered a series of explicit survey questions, which included validated measures of participants’ perceived gender identity (Luhtanen & Crocker, 1992), STEM identity (Chemers et al., 2011), and STEM stereotype endorsements (Schmader et al., 2004). Individual implicit and explicit balance identity scores were calculated based on the correspondence of Self-STEM, Self-Gender, and STEM-Gender IAT or survey scale scores.
Results First, a multiple regression analysis was conducted to determine if implicit balance scores varied as a function of female status or Science major status. The results indicated that Science majors reported higher implicit balance scores than Engineering/Computer Science majors (b1=0.41 p
Pedersen, R., & Sanneh, N., & Hernandez, P. R. (2022, February), Implicit and Explicit Balanced Identity Scores Vary as a Function of Gender and STEM Major Paper presented at 2022 CoNECD (Collaborative Network for Engineering & Computing Diversity) , New Orleans, Louisiana. https://peer.asee.org/39121
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