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Objective: The purpose of this study was to understand the experiences of historically underrepresented graduate students, more than half of whom were enrolled in science, technology, engineering, and mathematics (STEM) disciplines, during the COVID-19 pandemic. This focus group study represents an initial stage in developing an intervention for historically underrepresented graduate students and their families. Background: Underrepresentation of graduate students of color in STEM has been attributed to a myriad of factors, including a lack of support systems. Familial support is an endorsed reason for persisting in graduate school. It is unclear what historically underrepresented graduate students’ experiences are during uncertain times, such as a pandemic. Method: Focus groups were conducted online using a videoconferencing platform during the COVID-19 pandemic. Five focus groups included: historically underrepresented doctoral students (n =5), historically underrepresented master’s students (n = 6), academic faculty (n = 7), administrator, administrative faculty, and academic faculty (n = 6), and families of historically underrepresented doctoral students (n = 6). Data were analyzed using thematic analysis. Results: Historically underrepresented graduate students experienced difficulties in accessing resources, adjustments to home and family life, amplification of existing nonfinancial issues, and expressed both fears of and hopes for the future. Conclusion: The COVID-19 pandemic exacerbated existing inequalities in access to resources as well as nonfinancial family support. Implications: This study may help normalize historically underrepresented graduate students’ experiences during the COVID-19 pandemic. The findings include ideas for informing families about graduate school that can enlighten family support efforts for historically underrepresented graduate students and their families. 

Artificial intelligence (AI) tools and technologies are increasingly prevalent in society. Many teens interact with AI devices on a daily basis but often have a limited understanding of how AI works, as well as how it impacts society more broadly. It is critical to develop youths’ understanding of AI, cultivate ethical awareness, and support diverse youth in pursuing computer science to help ensure future development of more equitable AI technologies. Here, we share our experiences developing and remotely facilitating an interdisciplinary AI ethics program for secondary students designed to increase teens’ awareness and understanding of AI and its societal impacts. Students discussed stories with embedded ethical dilemmas, engaged with AI media and simulations, and created digital products to express their stance on an AI ethics issue. Across four iterations in formal and informal settings, we found students to be engaged in AI stories and invested in learning about AI and its societal impacts. Short stories were effective in raising awareness, focusing discussion and supporting students in developing a more nuanced understanding of AI ethics issues, such as fairness, bias and privacy. 

Predictive models for the Earth's space environment routinely use parameters from the solar wind as inputs. Measurements from spacecraft orbiting the first Lagrange point serve as convenient values for these inputs. The mass, momentum, and energy input into the Earth's space environment, however, are a function of the shocked and processed plasma within the magnetosheath, which can vary significantly from the pristine solar wind at the first Lagrange point. Here statistical measurements from the OMNI data set are combined with measurements by the THEMIS mission within the magnetosheath to generate uncertainty values for pressure and magnetic clock angle. These uncertainties are generated to account for known physical processes in the foreshock and magnetosheath as well as the position of the spacecraft being used to generate the OMNI data set.