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  1. As high school computer science course offerings have expanded over the past decade, gaps in race and gender have remained. This study embraces the “All” in the “CS for All” movement by shifting beyond access and toward abolitionist computer science teaching. Using data from professional development observations and interviews, we lift the voices of BIPOC CS teachers and bring together tenets put forth by Love (2019) for abolitionist teaching along with how these tenets map onto the work occurring in CS classrooms. Our findings indicate the importance of BIPOC teacher representation in CS classrooms and ways abolitionist teaching tenets can inform educator’s efforts at moving beyond broadening participation and toward radical inclusion, educational freedom, and self-determination, for ALL.
  2. Creating data visualizations requires diverse skills including computer programming, statistics, and graphic design. Visualization practitioners, often formally trained in one but not all of these areas, increasingly face the challenge of reconciling, integrating and prioritizing competing disciplinary values, norms and priorities. To inform multidisciplinary visualization pedagogy, we analyze the negotiation of values in the rhetoric and affordances of two common tools for creating visual representations of data: R and Adobe Illustrator. Features of, and discourse around, these standard visualization tools illustrate both a convergence of values and priorities (clear, attractive, and communicative data-driven graphics) side-by-side with a retention of rhetorical divisions between disciplinary communities (statistical analysis in contrast to creative expression). We discuss implications for data-driven work and data science curricula within the current environment where data visualization practice is converging while values in rhetoric remain divided.