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1. Can discussion boards disrupt gendered and racialized discussion patterns in math classes.

   Kim, M ( January 2022 , Proceedings of the Annual Conference on Research in Undergraduate Mathematics Education)

   Karunakaran, S. ; Higgins, A. (Ed.)

   Social Network Analysis is a method to analyze individuals’ social accessibility and power. We adapt it to change inequitable issues in STEM postsecondary education. Equity issues in mathematics education, such as underrepresented women and racial disparities, are prevalent. With the social capital perspective, we investigate the demographic characteristics of influential students and their social networks. Seventeen participants are undergraduate students in an inquiry-oriented linear algebra course. The number of nominations on discussion boards as “Shout-out” is data to measure influence and map the social network. By analyzing data with UCINET, we found that (1) the most influential students are non-White males and the principal components of the network are male-dominant, and (2) there is a female-dominant small cluster and female students have reciprocal networks. This study suggests further discussions of (1) how discussion boards position students with the social capital perspective and (2) intersectionality, especially for women of color. 

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2. Can discussion boards disrupt gendered and racialized discussion patterns in math classes?

   Kim, M. ; Andrews-Larson, C. ( January 2022 , Proceedings of the Annual Conference on Research in Undergraduate Mathematics Education)

   Karunakaran, S. ; Higgins, A. (Ed.)

   Social Network Analysis is a method to analyze individuals’ social accessibility and power. We adapt it to change inequitable issues in STEM postsecondary education. Equity issues in mathematics education, such as underrepresented women and racial disparities, are prevalent. With the social capital perspective, we investigate the demographic characteristics of influential students and their social networks. Seventeen participants are undergraduate students in an inquiry-oriented linear algebra course. The number of nominations on discussion boards as “Shout-out” is data to measure influence and map the social network. By analyzing data with UCINET, we found that (1) the most influential students are non-White males and the principal components of the network are male-dominant, and (2) there is a female-dominant small cluster and female students have reciprocal networks. This study suggests further discussions of (1) how discussion boards position students with the social capital perspective and (2) intersectionality, especially for women of color. 

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3. Leveraging Social Capital to Broaden Participation in STEM

   https://doi.org/10.1177/2372732219895997  

   Saw, Guan K. ( March 2020 , Policy Insights from the Behavioral and Brain Sciences)

   Broadening participation in science, technology, engineering, and mathematics (STEM) is critical to the nation’s economic growth and national security. In K–12 and higher education, researchers and educators increasingly employ the concept of social capital to develop programs for improving STEM learning, motivation, and participation of young students. STEM social capital in education comprises STEM-oriented resources—whether instrumental, informational, or emotional—that students access through their social networks. Major theoretical perspectives, research evidence, and promising practices are associated with the concepts of social capital in STEM education. Students’ social capital in STEM education (derived from families, peers, teachers, and professional networks) demonstrably promotes their STEM educational outcomes and career paths. Inclusive STEM schools, mentoring, and after-school programs are some promising approaches that can enhance STEM social capital and outcomes of underrepresented students, particularly women, Blacks/Hispanics/Native Americans, youth with low socioeconomic status, and persons with disabilities. 

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4. What You Need to Succeed: Examining Culture and Capital in Biomedical Engineering Undergraduate Education

   Corple, D. ; Zoltowski, C. B. ; Eddington, S. M. ; Brightman, A. O. ; Buzzanell, P. M ( June 2019 , ASEE annual conference & exposition proceedings)

   The low numbers of women and underrepresented minorities in engineering has often been characterized as a ‘pipeline problem,’ wherein few members of these groups choose engineering majors or ‘leak out’ of the engineering education pipeline before graduating [1]. Within this view, the difficulty of diversifying the engineering workforce can be addressed by stocking the pipeline with more diverse applicants. However, the assumption that adding more underrepresented applicants will solve the complex and persistent issues of diversity and inclusion within engineering has been challenged by recent research. Studies of engineering culture highlight how the persistence of women and minorities is linked to norms and assumptions of engineering cultures (e.g., [2], [3]). For example, some engineering cultures have been characterized as masculine, leading women to feel that they must become ‘one of the guys’ to fit in and be successful (e.g., [4]). In the U.S., engineering cultures are also predominantly white, which can make people of color feel unwelcome or isolated [5]. When individuals feel unwelcome in engineering cultures, they are likely to leave. Thus, engineering culture plays an important role in shaping who participates and successfully persists in engineering education and practice. Likewise, disciplinary cultures in engineering education also carry assumptions about what resources students should possess and utilize throughout their professional development. For example, educational cultures may assume students possess certain forms of ‘academic capital,’ such as rigorous training in STEM subjects prior to college. They might also assume students possess ‘navigational capital,’ or the ability to locate and access resources in the university system. However, these cultural assumptions have implications for the diversity and inclusivity of educational environments, as they shape what kinds of students are likely to succeed. For instance, first generation college (FGC) students may not possess the same navigational capital as continuing generation students [5]. Under-represented minority (URM) students often receive less pre-college training in STEM than their white counterparts [6]. However, FGC and URM students possess many forms of capital that often are unrecognized by education systems, for example, linguistic capital, or the ability to speak in multiple languages and styles) [7], [8]. Educational cultures that assume everyone possesses the same kinds of capital (i.e. that of white, American, high SES, and continuing generation students) construct barriers for students from diverse backgrounds. Thus, we propose that examining culture is essential for understanding the underlying assumptions and beliefs that give rise to the challenging issues surrounding the lack of diversity and inclusion in engineering. This case study examines the culture of a biomedical engineering (BME) program at a large Midwestern university and identifies underlying assumptions regarding what sources of cultural and social capital undergraduate students need to be successful. By tracing when and how students draw upon these forms of capital during their professional development, we examine the implications for students from diverse backgrounds, particularly FGC and URM students. 

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5. Social capital I: measurement and associations with economic mobility

   https://doi.org/10.1038/s41586-022-04996-4  

   Chetty, Raj ; Jackson, Matthew O. ; Kuchler, Theresa ; Stroebel, Johannes ; Hendren, Nathaniel ; Fluegge, Robert B. ; Gong, Sara ; Gonzalez, Federico ; Grondin, Armelle ; Jacob, Matthew ; et al ( August 2022 , Nature)

   Abstract Social capital—the strength of an individual’s social network and community—has been identified as a potential determinant of outcomes ranging from education to health 1–8 . However, efforts to understand what types of social capital matter for these outcomes have been hindered by a lack of social network data. Here, in the first of a pair of papers 9 , we use data on 21 billion friendships from Facebook to study social capital. We measure and analyse three types of social capital by ZIP (postal) code in the United States: (1) connectedness between different types of people, such as those with low versus high socioeconomic status (SES); (2) social cohesion, such as the extent of cliques in friendship networks; and (3) civic engagement, such as rates of volunteering. These measures vary substantially across areas, but are not highly correlated with each other. We demonstrate the importance of distinguishing these forms of social capital by analysing their associations with economic mobility across areas. The share of high-SES friends among individuals with low SES—which we term economic connectedness—is among the strongest predictors of upward income mobility identified to date 10,11 . Other social capital measures are not strongly associated with economic mobility. If children with low-SES parents were to grow up in counties with economic connectedness comparable to that of the average child with high-SES parents, their incomes in adulthood would increase by 20% on average. Differences in economic connectedness can explain well-known relationships between upward income mobility and racial segregation, poverty rates, and inequality 12–14 . To support further research and policy interventions, we publicly release privacy-protected statistics on social capital by ZIP code at https://www.socialcapital.org . 

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