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1. Disproportionate impacts of COVID-19 on marginalized and minoritized early-career academic scientists

   https://doi.org/10.1371/journal.pone.0274278  

   Douglas, Hannah M. ; Settles, Isis H. ; Cech, Erin A. ; Montgomery, Georgina M. ; Nadolsky, Lexi R. ; Hawkins, Arika K. ; Ma, Guizhen ; Davis, Tangier M. ; Elliott, Kevin C. ; Cheruvelil, Kendra Spence ( September 2022 , PLOS ONE)

   Grundy, Quinn (Ed.)

   Early research on the impact of COVID-19 on academic scientists suggests that disruptions to research, teaching, and daily work life are not experienced equally. However, this work has overwhelmingly focused on experiences of women and parents, with limited attention to the disproportionate impact on academic work by race, disability status, sexual identity, first-generation status, and academic career stage. Using a stratified random survey sample of early-career academics in four science disciplines ( N = 3,277), we investigated socio-demographic and career stage differences in the effect of the COVID-19 pandemic along seven work outcomes: changes in four work areas (research progress, workload, concern about career advancement, support from mentors) and work disruptions due to three COVID-19 related life challenges (physical health, mental health, and caretaking). Our analyses examined patterns across career stages as well as separately for doctoral students and for postdocs/assistant professors. Overall, our results indicate that scientists from marginalized (i.e., devalued) and minoritized (i.e., underrepresented) groups across early career stages reported more negative work outcomes as a result of COVID-19. However, there were notable patterns of differences depending on the socio-demographic identities examined. Those with a physical or mental disability were negatively impacted on all seven work outcomes. Women, primary caregivers, underrepresented racial minorities, sexual minorities, and first-generation scholars reported more negative experiences across several outcomes such as increased disruptions due to physical health symptoms and additional caretaking compared to more privileged counterparts. Doctoral students reported more work disruptions from life challenges than other early-career scholars, especially those related to health problems, while assistant professors reported more negative changes in areas such as decreased research progress and increased workload. These findings suggest that the COVID-19 pandemic has disproportionately harmed work outcomes for minoritized and marginalized early-career scholars. Institutional interventions are required to address these inequalities in an effort to retain diverse cohorts in academic science. 

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2. Internship Prevalence and Factors Related to Participation

   Atwood, S. A. ; Gilmartin, S. K. ; Mostoller, A. M. ; Chen, H. L. ; Sheppard, S. ( January 2021 , 2021 ASEE Virtual Annual Conference)

   null (Ed.)

   The value of internship experiences for engineering students is widely discussed in the literature. With this analysis, we seek to contribute knowledge addressing 1) the prevalence of internship experiences amongst engineering students drawn from a large, multi-institutional, nationally-representative sample, 2) if the likelihood of having an engineering internship experiences is equitable amongst various student identities, and 3) what additional factors influence the likelihood of a student having an internship experience, such as field of study and institution type. Data were drawn from a 2015 multi-institutional nationally representative survey of engineering juniors and seniors, excluding one institution with a mandatory co-op program (n = 5530 from 26 institutions). A z-test was used to analyze differences in internship participation rates related to academic cohort (e.g., junior, senior), gender, underrepresented minority (URM) status, first-generation, and low-income status, as well as a subset of identities at the intersection of these groups (gender + URM; first-generation + low-income). A logistic regression model further examined factors such as GPA, engineering task self-efficacy, field of engineering, and institution type. We found that amongst the students in our dataset, 64.7% of the seniors had “worked in a professional engineering environment as an intern/co-op” (41.1% of juniors, 64.7% of 5th years). Significantly less likely (p<0.05) to have internship experiences were men compared to women (52.9% vs 58.3%), URM students compared to their majority counterparts (41.5% vs 56.8%), first-generation students compared to continuing (47.6% vs 57.2%), and low-income students compared to higher-income peers (46.2% vs 57.4%). Examined intersectional identities significantly less likely to have an internship were URM men (37.5%) and first-generation low-income students (42.0%), while non-URM women (60.5%) and continuing high-income students (58.2%) were most likely to report having an internship. Results from the logistic regression model indicate that significant factors are cohort (junior vs senior), GPA, engineering task self-efficacy, and engineering field. When controlling for the other variables in the model, gender, URM, first-generation, and low-income status remain significant; however, the interaction effect between these identities is not significant in the full model. Institution type did not have much impact. Having a research experience was not a significant factor in predicting the likelihood of having an internship experience, although studying abroad significantly increased the odds. Amongst engineering fields, industrial and civil engineering students were the most likely to have an internship, while aerospace and materials engineering students were the least likely. Full results and discussion will be presented in the paper. This analysis provides valuable information for a variety of stakeholders. For engineering programs, it is useful to benchmark historic students’ rates of internship participation against a multi-institutional, nationally representative dataset. For academic advisors and career services professionals, it is useful to understand in which fields an internship is common to be competitive on the job market, and which fields have fewer opportunities or prioritize research experiences. Ultimately, for those in higher education and workforce development it is vital to understand which identities, and intersectional identities, are accessing internship experiences as a pathway into the engineering workforce. 

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3. Defining First-generation and Low-income Students in Engineering: An Exploration

   https://doi.org/10.18260/1-2--34373  

   Atwood, Sara A ; Gilmartin, Shannon K ; Harris, Angela ; Sheppard, Sheri ( January 2020 , ASEE Annual Conference proceedings)

   First-generation (FG) and/or low-income (LI) engineering student populations are of particular interest in engineering education. However, these populations are not defined in a consistent manner across the literature or amongst stakeholders. The intersectional identities of these groups have also not been fully explored in most quantitative-based engineering education research. This research paper aims to answer the following three research questions: (RQ1) How do students’ demographic characteristics and college experiences differ depending on levels of parent educational attainment (which forms the basis of first-generation definitions) and family income? (RQ2) How do ‘first-generation’ and ‘low-income’ definitions impact results comparing to their continuing-generation and higher-income peers? (RQ3) How does considering first-generation and low-income identities through an intersectional lens deepen insight into the experiences of first-generation and low-income groups? Data were drawn from a nationally representative survey of engineering juniors and seniors (n = 6197 from 27 U.S. institutions). Statistical analyses were conducted to evaluate respondent differences in demographics (underrepresented racial/ethnic minority (URM), women, URM women), college experiences (internships/co-ops, having a job, conducting research, and study abroad), and engineering task self-efficacy (ETSE), based on various definitions of ‘first generation’ and ‘low income’ depending on levels of parental educational attainment and self-reported family income. Our results indicate that categorizing a first-generation student as someone whose parents have less than an associate’s degree versus less than a bachelor’s degree may lead to different understandings of their experiences (RQ1). For example, the proportion of URM students is higher among those whose parents have less than an associate’s degree than among their “associate’s degree or more” peers (26% vs 11.9%). However, differences in college experiences are most pronounced among students whose parents have less than a bachelor’s degree compared with their “bachelor’s degree or more” peers: having a job to help pay for college (55.4% vs 47.3%), research with faculty (22.7% vs 35.0%), and study abroad (9.0% vs 17.3%). With respect to differences by income levels, respondents are statistically different across income groups, with fewer URM students as family income level increases. As family income level increases, there are more women in aggregate, but fewer URM women. College experiences are different for the middle income or higher group (internship 48.4% low and lower-middle income vs 59.0% middle income or higher; study abroad 11.2% vs 16.4%; job 58.6% vs 46.8%). Despite these differences in demographic characteristics and college experiences depending on parental educational attainment and family income, our dataset indicates that the definition does not change the statistical significance when comparing between first-generation students and students who were continuing-generation by any definition (RQ2). First-generation and low-income statuses are often used as proxies for one another, and in this dataset, are highly correlated. However, there are unique patterns at the intersection of these two identities. For the purpose of our RQ3 analysis, we define ‘first-generation’ as students whose parents earned less than a bachelor’s degree and ‘low-income’ as low or lower-middle income. In this sample, 68 percent of students were neither FG nor LI while 11 percent were both (FG&LI). On no measure of demographics or college experience is the FG&LI group statistically similar to the advantaged group. Low-income students had the highest participation in working to pay for college, regardless of parental education, while first-generation students had the lower internship participation than low-income students. Furthermore, being FG&LI is associated with lower ETSE compared with all other groups. These results suggest that care is required when applying the labels “first-generation” and/or “low-income” when considering these groups in developing institutional support programs, in engineering education research, and in educational policy. Moreover, by considering first-generation and low-income students with an intersectional lens, we gain deeper insight into engineering student populations that may reveal potential opportunities and barriers to educational resources and experiences that are an important part of preparation for an engineering career. 

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4. Fly-CURE, a multi-institutional CURE using Drosophila , increases students' confidence, sense of belonging, and persistence in research

   https://doi.org/10.1128/jmbe.00245-22  

   Merkle, Julie A. ; Devergne, Olivier ; Kelly, Seth M. ; Croonquist, Paula A. ; Evans, Cory J. ; Hwalek, Melanie A. ; Straub, Victoria L. ; Hamill, Danielle R. ; Peister, Alexandra ; Puthoff, David P. ; et al ( September 2023 , Journal of Microbiology & Biology Education)

   Wang, Jack (Ed.)

   The Fly-CURE is a genetics-focused multi-institutional Course-Based Undergraduate Research Experience (CURE) that provides undergraduate students with hands-on research experiences within a course. Through the Fly-CURE, undergraduate students at diverse types of higher education institutions across the United States map and characterize novel mutants isolated from a genetic screen in Drosophila melanogaster . To date, more than 20 mutants have been studied across 20 institutions, and our scientific data have led to eleven publications with more than 500 students as authors. To evaluate the impact of the Fly-CURE experience on students, we developed and validated assessment tools to identify students’ perceived research self-efficacy, sense of belonging in science, and intent to pursue additional research opportunities. Our data, collected over three academic years and involving 14 institutions and 480 students, show gains in these metrics after completion of the Fly-CURE across all student subgroups analyzed, including comparisons of gender, academic status, racial and ethnic groups, and parents’ educational background. Importantly, our data also show differential gains in the areas of self-efficacy and interest in seeking additional research opportunities between Fly-CURE students with and without prior research experience, illustrating the positive impact of research exposure (dosage) on student outcomes. Altogether, our data indicate that the Fly-CURE experience has a significant impact on students’ efficacy with research methods, sense of belonging to the scientific research community, and interest in pursuing additional research experiences. 

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5. A latent class analysis approach to the identification of doctoral students at risk of attrition

   https://doi.org/10.1371/journal.pone.0280325  

   Stevens, Samantha M. ; Ruberton, Peter M. ; Smyth, Joshua M. ; Cohen, Geoffrey L. ; Purdie Greenaway, Valerie ; Cook, Jonathan E. ( January 2023 , PLOS ONE)

   Benetreau, Yann (Ed.)

   To advance understanding of doctoral student experiences and the high attrition rates among Science, Technology, Engineering, and Mathematics (STEM) doctoral students, we developed and examined the psychological profiles of different types of doctoral students. We used latent class analysis on self-reported psychological data relevant to psychological threat from 1,081 incoming doctoral students across three universities and found that the best-fitting model delineated four threat classes: Lowest Threat , Nonchalant , Engaged/Worried , and Highest Threat . These classes were associated with characteristics measured at the beginning of students’ first semester of graduate school that may influence attrition risk, including differences in academic preparation (e.g., amount of research experience), self-evaluations and perceived fit (e.g., sense of belonging), attitudes towards graduate school and academia (e.g., strength of motivation), and interpersonal relations (e.g., perceived social support). Lowest Threat students tended to report the most positive characteristics and Highest Threat students the most negative characteristics, whereas the results for Nonchalant and Engaged/Worried students were more mixed. Ultimately, we suggest that Engaged/Worried and Highest Threat students are at relatively high risk of attrition. Moreover, the demographic distributions of profiles differed, with members of groups more likely to face social identity threat (e.g., women) being overrepresented in a higher threat profile (i.e., Engaged/Worried students) and underrepresented in lower threat profiles (i.e., Lowest Threat and Nonchalant students). We conclude that doctoral students meaningfully vary in their psychological threat at the beginning of graduate study and suggest that these differences may portend divergent outcomes. 

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