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  1. Abstract Background

    We used an opportunity gap framework to analyze the pathways through which students enter into and depart from science, technology, engineering, and mathematics (STEM) degrees in an R1 higher education institution and to better understand the demographic disparities in STEM degree attainment.

    Results

    We found disparities in 6-year STEM graduation rates on the basis of gender, race/ethnicity, and parental education level. Using mediation analysis, we showed that the gender disparity in STEM degree attainment was explained by disparities in aspiration: a gender disparity in students’ intent to pursue STEM at the beginning of college; women were less likely to graduate with STEM degrees because they were less likely to intend to pursue STEM degrees. However, disparities in STEM degree attainment across race/ethnicities and parental education level were largely explained by disparities in attrition: persons excluded because of their ethnicity or race (PEERs) and first generation students were less likely to graduate with STEM degrees due to fewer academic opportunities provided prior to college (estimated using college entrance exams scores) and more academic challenges during college as captured by first year GPAs.

    Conclusions

    Our results reinforce the idea that patterns of departure from STEM pathways differ among marginalized groups. To promote and retain students in STEM, it is critical that we understand these differing patterns and consider structural efforts to support students at different stages in their education.

     
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  2. Abstract

    Sexual and gender minorities face considerable inequities in society, including in science. In biology, course content provides opportunities to challenge harmful preconceptions about what is “natural” while avoiding the notion that anything found in nature is inherently good (the appeal-to-nature fallacy). We provide six principles for instructors to teach sex- and gender-related topics in postsecondary biology in a more inclusive and accurate manner: highlighting biological diversity early, presenting the social and historical context of science, using inclusive language, teaching the iterative process of science, presenting students with a diversity of role models, and developing a classroom culture of respect and inclusion. To illustrate these six principles, we review the many definitions of sex and demonstrate applying the principles to three example topics: sexual reproduction, sex determination or differentiation, and sexual selection. These principles provide a tangible starting place to create more scientifically accurate, engaging, and inclusive classrooms.

     
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  3. Bolger, Molly (Ed.)
    Traditional biology curricula depict science as an objective field, overlooking the important influence that human values and biases have on what is studied and who can be a scientist. We can work to address this shortcoming by incorporating ideological awareness into the curriculum, which is an understanding of biases, stereotypes, and assumptions that shape contemporary and historical science. We surveyed a national sample of lower-level biology instructors to determine 1) why it is important for students to learn science, 2) the perceived educational value of ideological awareness in the classroom, and 3) hesitancies associated with ideological awareness implementation. We found that most instructors reported “understanding the world” as the main goal of science education. Despite the perceived value of ideological awareness, such as increasing student engagement and dispelling misconceptions, instructors were hesitant to implement ideological awareness modules due to potential personal and professional consequences. 
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    Free, publicly-accessible full text available September 1, 2024
  4. Georgiou, H. (Ed.)
    Addressing the challenges facing society and the world will require an understanding of the biases and limitations of science. To combat these challenges, here, we advocate for the incorporation of ideologically aware (IA) material into postsecondary biology curricula. IA materials communicate to students how biases, assumptions, and stereotypes inform approaches to and outcomes of science. By engaging with IA materials, student awareness of the impact of science on social problems is expected to increase. In this paper, we situate this IA approach with two other pedagogical approaches that incorporate societally relevant content: culturally relevant pedagogy and socioscientific issues. We then call for research to test ways of supporting instructor implementation of IA material, to evaluate the impact of IA topics on student academic and sociopsychological outcomes, and to explore how to implement IA material in different cultural and social settings. Throughout, we focus on IA topics in the context of postsecondary biology classrooms but encourage the incorporation of IA materials across scientific disciplines and educational settings. Our hope is that greater inclusion of IA materials will create more transparent, scientifically accurate, and inclusive classrooms. 
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  5. null (Ed.)
    Authentic, “messy data” contain variability that comes from many sources, such as natural variation in nature, chance occurrences during research, and human error. It is this messiness that both deters potential users of authentic data and gives data the power to create unique learning opportunities that reveal the nature of science itself. While the value of bringing contemporary research and messy data into the classroom is recognized, implementation can seem overwhelming. We discuss the importance of frequent interactions with messy data throughout K–16 science education as a mechanism for students to engage in the practices of science, such as visualizing, analyzing, and interpreting data. Next, we describe strategies to help facilitate the use of messy data in the classroom while building complexity over time. Finally, we outline one potential sequence of activities, with specific examples, to highlight how various activity types can be used to scaffold students' interactions with messy data. 
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