Understanding persistent gender gaps in STEM

Picturing mathematicians: Examining how gender and math anxiety relate to students' representations of mathematicians in late elementary and middle school

A common gender stereotype is that men are higher performers than women in math. This stereotype not only affects students' math performance but also influences their interests and vocational options in science, technology, engineering, and mathematics (STEM). The "Draw-a-Mathematician Task" (DAMT) has been used to understand students' perceptions of who is a mathematician. However, the existing studies with DAMT often do not consider the role of other individual traits that are closely associated with gender stereotypes, such as math anxiety. The current study examined how students' math anxiety, gender, and grade level may be associated with their gendered representations of mathematicians and the level of math difficulty included in their drawings. Students (N = 261; 133 girls, 128 boys; 116 fourth graders, 89 sixth graders, 56 eighth graders) completed a math anxiety questionnaire and were then asked to draw a picture of a mathematician and explain where their ideas came from. Overall, girls drew more female mathematicians than boys, and the proportion of students drawing female mathematicians dropped steeply in eighth grade, particularly for girls. Girls showed higher levels of math anxiety than boys, and math anxiety increased across grades. However, math anxiety was unrelated to the content of students' drawings. This study emphasizes the importance of efforts to support girls' sense of belonging in mathematics, especially into secondary grades in which reported levels of math anxiety are higher.

Divergence in children's gender stereotypes and motivation across STEM fields

STEM disciplines are traditionally stereotyped as being for men and boys. However, in two preregistered studies of Grades 1 to 12 students in the United States (N = 2,765), we find a significant divergence in students' gender stereotypes about different STEM fields. Gender stereotypes about computer science and engineering more strongly favored boys than did gender stereotypes about math and science. These patterns hold across genders, intersections of gender and race/ethnicity, and two geographical regions. This divergence between different STEM fields was evident, although smaller, for children in elementary school compared to adolescents (students in middle school and high school). The divergence in stereotypes predicted students' divergence in motivation for entering these fields. Gender stereotypes on average slightly favored girls in math and were egalitarian or slightly favored girls in science, while boys remained strongly favored for computer science and engineering, with implications for educational equity and targeted interventions.

Gender and racial diversity socialization in science

Scientific collaboration networks are a form of unequally distributed social capital that shapes both researcher job placement and long-term research productivity and prominence. However, the role of collaboration networks in shaping the gender and racial diversity of the scientific workforce remains unclear. Here we propose a computational null model to investigate the degree to which early-career scientific collaborators with representationally diverse cohorts of scholars are associated with forming or participating in more diverse research groups as established researchers. When testing this hypothesis using two large-scale, longitudinal datasets on scientific collaborations, we find that the gender and racial diversity in a researcher's early-career collaboration environment is strongly associated with the diversity of their collaborators in their established period. This diversity-association effect is particularly prominent for men. Coupled with gender and racial homophily between advisors and advisees, collaborator diversity represents a generational effect that partly explains why changes in representation within the scientific workforce tend to happen very slowly.

Shifting Perspectives: A Community-Based Learning Science Outreach Course That Engages Undergraduate Metacognition through Midsemester Redesign

The content and implementation of a one-credit course with built-in science outreach to the community partner, Girls, Inc., is described herein. This community-based learning (CBL) course aims at developing the undergraduates' ability to plan, monitor, evaluate, and adjust to new learning environments by reflecting on their own learning and also to define their scientific identities. The course delivery is divided into five Training and Preparation sessions, seven Community Partner Interaction sessions, and two Assessment sessions. Throughout the semester, the participating students reflected on their experiences and contextualized the outreach within the educational theories discussed. Student feedback indicated a shift in the undergraduate students' bias on gender in science, and the appreciation to have the opportunity for metacognitive reflection.

Enhanced conceptual understanding through formative assessment: results of a randomized controlled intervention study in physics classes

While formative assessment is a widely valued instructional approach to support meaningful learning, putting it into classroom practice remains a challenge, also because the time resources required may conflict with other goals. In a cluster-randomized controlled intervention study with 29 teachers and 604 students (mean age 15.6 years) at secondary school level, we examined the yield of formative assessment with regard to students' conceptual understanding and quantitative problem-solving skills in physics. Ten teachers applied formative assessment (FA group) in a 14-lesson curriculum on kinematics after having undergone a training that focused on the implementation of multiple-choice concept questions together with monitoring tools, clicker sessions, and reflective lessons. In the frequent testing group (FT group), ten teachers had no training on formative assessment but implemented the same concept questions as those used in the FA group. Nine teachers taught kinematics in their traditional way (TT group). The results revealed that students in the FA group outperformed students in the other two groups in a test on conceptual understanding immediately after the intervention as well as 3 months later, whereas students from the FT group and the TT group did not differ. Importantly, a better conceptual understanding in the FA group was not at the expense of performance in quantitative problem solving, as students of this group better integrated both kinds of knowledge. Our study has shown that a short but well-structured formative assessment teacher training could unfold its potential in terms of students' learning of challenging content.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11092-024-09445-6.

An institution-level analysis of gender gaps in STEM over time

Gender gaps in engineering and computer science narrow at math-selective schools and widen in others.

Family science capital moderates gender differences in parent-child scientific conversation

This study examined whether variation in parent-child conversations about scientific processes can be explained by child gender and the science-related resources available to parents, known as scientific capital. Parents of 4- and 5-year-old children (N = 70) from across the United States completed a survey of science capital and were then videotaped with their children at home interacting with two science activities (i.e., balance scale and circuit toy). Videos were transcribed and analyzed for parents' science process language. Results indicated that parents' science process language occurred significantly more often during conversations with boys, among families with higher levels of scientific capital, and during the scale activity. Gender differences in science process language were not apparent at higher levels of science capital and during the scale activity. These effects speak to the need for measuring child, family, and contextual characteristics when identifying factors that promote children's early science engagement and learning. Results are discussed in terms of future interventions that could build scientific capital as a means to counteract stereotypes around gender and science.

Comparative analysis of automatic gender detection from names: evaluating the stability and performance of ChatGPT versus Namsor, and Gender-API

The gender classification from names is crucial for uncovering a myriad of gender-related research questions. Traditionally, this has been automatically computed by gender detection tools (GDTs), which now face new industry players in the form of conversational bots like ChatGPT. This paper statistically tests the stability and performance of ChatGPT 3.5 Turbo and ChatGPT 4o for gender detection. It also compares two of the most used GDTs (Namsor and Gender-API) with ChatGPT using a dataset of 5,779 records compiled from previous studies for the most challenging variant, which is the gender inference from full name without providing any additional information. Results statistically show that ChatGPT is very stable presenting low standard deviation and tight confidence intervals for the same input, while it presents small differences in performance when prompt changes. ChatGPT slightly outperforms the other tools with an overall accuracy over 96%, although the difference is around 3% with both GDTs. When the probability returned by GDTs is factored in, differences get narrower and comparable in terms of inter-coder reliability and error coded. ChatGPT stands out in the reduced number of non-classifications (0% in most tests), which in combination with the other metrics analyzed, results in a solid alternative for gender inference. This paper contributes to current literature on gender detection classification from names by testing the stability and performance of the most used state-of-the-art AI tool, suggesting that the generative language model of ChatGPT provides a robust alternative to traditional gender application programming interfaces (APIs), yet GDTs (especially Namsor) should be considered for research-oriented purposes.

Behavioral and Psychosocial Dynamics of Engagement: The Digital Divide in Artificial Intelligence [AI]-Driven Sports Podcasts

The digital divide, particularly within the context of Artificial Intelligence (AI) sport podcasts, presents significant behavioral and psychosocial challenges for student engagement. This study examines the disparities in access to and proficiency with Information Communication Technologies (ICTs) across different demographic groups, focusing on gender, age, and religious level. The advent of the commercial web has heightened the significance of these divides, as the first-level digital divide concerns access to the internet, while the second-level digital divide pertains to the ability to use technology proficiently. The existing literature has consistently highlighted persistent inequalities in these areas, which significantly impact the extent to which students from various backgrounds can engage with AI sport podcasts effectively. Understanding these dynamics is crucial for developing strategies to bridge the gap and ensure equitable access to digital learning resources.

Gendered Performance Gaps in an Upper-Division Biology Course: Academic, Demographic, Environmental, and Affective Factors

Despite the existent gender parity in undergraduate biology degree attainment, gendered differences in outcomes are prevalent in introductory biology courses. Less is known about whether these disparities persist at the upper-division level, after most attrition is assumed to have occurred. Here, we report the consistent presence of gender equity gaps across 35 offerings (10 years) of a large-enrollment upper-division biology course at a research-intensive public university. Multilevel modeling showed that women's grades were lower than men's, regardless of prior GPA. These gender gaps were present even when controlling for students' race/ethnicity, socioeconomic status, first-generation college-going status, international status, and transfer status. Class size, gender representation in the classroom, and instructor gender did not significantly relate to course grades. Student questionnaires in a subset of offerings indicated gendered differences in course anxiety, science identity, and science self-efficacy, which correlated with grade outcomes. These results suggest that women experience differential outcomes in upper-division biology, which may negatively influence their persistence in STEM fields postgraduation. Our findings suggest that gender disparities are a systemic problem throughout the undergraduate biology degree and underscore the need for further examination and transformation of upper-division courses to support all students, even at late stages of their degrees.

Gender bias in cultural tightness across the 50 US states, its correlates, and links to gender inequality in leadership and innovation

Cultural tightness theory, which holds that "tight" cultures have rigid norms and sanctions, provides unique insights into cultural variations. However, current theorizing has not analyzed gender differences in cultural tightness. Addressing this gap, this research shows that women are more constrained than men by norms within the same society. By recruiting 15,425 respondents, we mapped state-level gender bias in cultural tightness across the United States. Variability in gender bias in cultural tightness was associated with state-level sociopolitical factors (religion and political ideology) and gender-related threats. Gender bias in cultural tightness was positively associated with state-level gender inequality in (business and political) leadership and innovation, two major challenges faced by women professionals. Overall, this research advances cultural tightness theory and offers a cultural norms account on persistent gender inequalities in society.

Gender differences in the intention to study math increase with math performance

Even though females currently outnumber males in higher education, they remain largely underrepresented in math-related fields of study, with no sign of improvement during the past decades. To better understand which students drive this underrepresentation, we use PISA 2012 data on 251,120 15-year-old students in 61 countries to analyse boys' and girls' educational intentions along the ability distribution on math assessment tests. We analyze the percentages of boys and girls intending to pursue math-related studies or careers as a function of math performance. First, we show that for both boys and girls, there is a positive and linear relation between the probability of intending to pursue math and math performance. Second, the positive relation is stronger among boys than among girls. In particular, the gender gap in student intentions to pursue math-related studies or careers is close to zero among the poorest performers in math and increases steadily with math performance. Third, as a consequence, the gender gap in math performance, to the detriment of girls, is larger among students intending to pursue math than in the general student population.

Gender representation and academic achievement among STEM-interested students in college STEM courses

Substantial gender equity gaps in postsecondary degree completion persist within many science, technology, engineering, and mathematics (STEM) disciplines, and these disparities have not narrowed during the 21st century. Various explanations of this phenomenon have been offered; one possibility that has received limited attention is that the sparse representation of women itself has adverse effects on the academic achievement-and ultimately the persistence and graduation-of women who take STEM courses. This study explored the relationship between two forms of gender representation (i.e., the proportion of female students within a course and the presence of a female instructor) and grades within a sample of 11,958 STEM-interested undergraduates enrolled in 8686 different STEM courses at 20 colleges and universities. Female student representation within a course predicted greater academic achievement in STEM for all students, and these findings were generally stronger among female students than male students. Female students also consistently benefitted more than male students from having a female STEM instructor. These findings were largely similar across a range of student and course characteristics and were robust to different analytic approaches; a notable exception was that female student representation had particularly favorable outcomes for female students (relative to male students) within mathematics/statistics and computer science courses.

Alone or together: The role of gender and social context prior to Aha‐experiences

Prior research indicates that boys show more interest in science, technology, engineering, and mathematics (STEM) than girls do. Given that Aha-experiences yield positive affect and increase interest, the question arises whether there are gender differences in Aha-experiences that could help explain the gender differences in interest. Derived from social role theory, we hypothesized that men report having Aha-experiences alone, whereas women report having Aha-experiences together with others. In a retrospective survey study comprising three independent samples (N = 899), we conducted chi-square analyses to explore the relationship of gender, social context (alone; not alone), domain, and situational interest. Across all participants, we found that men were more probably alone and women more probably together with others when they had an Aha-experience. More fine-grained analyses revealed that the effect was especially pronounced when the Aha-experience increased situational interest within STEM or the personal domain. The study suggests that social context played a different role in the occurrence of Aha-experiences in men and women. We discuss the implications of our findings for STEM instruction at school.

The reciprocal relationship between mathematics self-efficacy and mathematics performance in US high school students: Instrumental variables estimates and gender differences

Objective

To investigate the reciprocal relationship between high school students’ academic self-efficacy and achievement in mathematics using US data from the HSLS:2009 and first follow-up longitudinal surveys, while accounting for biases in effect estimates due to unobserved heterogeneity.

Methods

Instrumental Variables (IV) regressions were estimated, to derive causal effect estimates of earlier math self-efficacy on later math achievement and vice versa. Particular attention was paid to testing the validity of instruments used. Models were estimated separately by gender, to uncover gender differences in effects.

Results

Evidence of robust reciprocal effects between self-efficacy and achievement for male students is presented, with the dominant effect from earlier achievement to later self-efficacy. For girls, evidence of such effects is weak. Generally, IV estimates are higher than OLS estimates for males, but not for females. As opposed to earlier correlational studies which did not find significant gender differences despite theoretical expectations for their existence, the findings support higher effects for male students.

Plugging the Leaky Pipeline:A Qualitative Investigation of Untenured Female Faculty in STEM

The current study set out to highlight the voices and stories of 129 female-identifying assistant professors in Science, Technology, Engineering, and Mathematics (STEM) who responded to open-ended questions regarding their perceived barriers, supports, and experiences on their journey toward tenure. The current study utilized Consensual Qualitative Research-Modified (CQR-M; Spangler et al., 2012 ) for the methodology and data analysis, as the current study included a relatively large number of women and brief qualitative data. Responses fell into four domains: barriers, supports, needed resources, and miscellaneous responses. Additionally, responses were compared between women in STEM fields with higher percentages of female faculty versus STEM fields with lower percentages of female faculty, with results indicating that women in STEM fields with lower gender equality reported more gender discrimination, more difficult colleagues, and less institutional or administrative supports and policies. Future directions and clinical implications are discussed.

Stereotypical descriptions of computer science career interests are not representative of many computer scientists

Using responses from a large respondent-initiated online survey, we find that the career interests of many current and aspiring computer scientists in the United States diverge from a popular and official depiction of computer scientists' interests used for career and workforce development worldwide. Distinct profiles of career interests emerged from the data. These profiles suggest that many women in the field value social and artistic expression in a way not currently recognized by established depictions of computer scientists' interests. Better capturing the diversity of interests in computer science might help to boost women's, and men's, engagement in this STEM field.

Turning the Tide for Academic Women in STEM: A Postpandemic Vision for Supporting Female Scientists

The "leaky pipeline" of women in science, technology, engineering, and mathematics (STEM), which is especially acute for academic mothers, continues to be problematic as women face continuous cycles of barriers and obstacles to advancing further in their fields. The severity and prevalence of the COVID-19 pandemic both highlighted and exacerbated the unique challenges faced by female graduate students, postdocs, research staff, and principal investigators because of lockdowns, quarantines, school closures, lack of external childcare, and heightened family responsibilities, on top of professional responsibilities. This perspective provides recommendations of specific policies and practices that combat stigmas faced by women in STEM and can help them retain their careers. We discuss actions that can be taken to support women within academic institutions, journals, government/federal centers, university-level departments, and individual research groups. These recommendations are based on prior initiatives that have been successful in having a positive impact on gender equity─a central tenet of our postpandemic vision for the STEM workforce.

Gender stereotypes about interests start early and cause gender disparities in computer science and engineering

Societal stereotypes that girls are less interested than boys in computer science and engineering are endorsed by children and adolescents in a large and socioeconomically diverse sample, across multiple racial/ethnic and gender intersections, and as early as age six (first grade). Gender-interest stereotypes may contribute to subsequent gender disparities in the pursuit of these societally important fields. Addressing interest stereotypes may help improve educational equity.

Societal stereotypes depict girls as less interested than boys in computer science and engineering. We demonstrate the existence of these stereotypes among children and adolescents from first to 12th grade and their potential negative consequences for girls’ subsequent participation in these fields. Studies 1 and 2 (n = 2,277; one preregistered) reveal that children as young as age six (first grade) and adolescents across multiple racial/ethnic and gender intersections (Black, Latinx, Asian, and White girls and boys) endorse stereotypes that girls are less interested than boys in computer science and engineering. The more that individual girls endorse gender-interest stereotypes favoring boys in computer science and engineering, the lower their own interest and sense of belonging in these fields. These gender-interest stereotypes are endorsed even more strongly than gender stereotypes about computer science and engineering abilities. Studies 3 and 4 (n = 172; both preregistered) experimentally demonstrate that 8- to 9-y-old girls are significantly less interested in an activity marked with a gender stereotype (“girls are less interested in this activity than boys”) compared to an activity with no such stereotype (“girls and boys are equally interested in this activity”). Taken together, both ecologically valid real-world studies (Studies 1 and 2) and controlled preregistered laboratory experiments (Studies 3 and 4) reveal that stereotypes that girls are less interested than boys in computer science and engineering emerge early and may contribute to gender disparities.

Audiovisual Content to Promote Women Scientists on the YouTube Channels of Spanish Biosanitary Research Institutes

YouTube is an appropriate social network for disseminating scientific audiovisual content, and this content can help to make the position of women in science, and gender equality, more visible. The aim of this study is to analyse the visibility of women scientists on the YouTube channels of Spanish biosanitary research institutes accredited by the Instituto de Salud Carlos III. A mixed study of the channels and communication departments of the institutions has been carried out, analysing metrics of audience impact, the type of audiovisual production and the use of YouTube in the institution. Of the 1914 videos analysed, 4% (n = 76) of the content is related to the visibility of women scientists and has little impact. The audiovisual production is basic and informative, without a dramatic narrative structure and focused on transmitting the personal experiences of women scientists. It is necessary to invest resources in institutions to improve the production and dissemination of content that makes women in the scientific field more visible, especially among students.