<p style='text-indent:20px;'>While coursework provides undergraduate data science students with some relevant analytic skills, many are not given the rich experiences with data and computing they need to be successful in the workplace. Additionally, students often have limited exposure to team-based data science and the principles and tools of collaboration that are encountered outside of school.</p><p style='text-indent:20px;'>In this paper, we describe the DSC-WAV program, an NSF-funded data science workforce development project in which teams of undergraduate sophomores and juniors work with a local non-profit organization on a data-focused problem. To help students develop a sense of agency and improve confidence in their technical and non-technical data science skills, the project promoted a team-based approach to data science, adopting several processes and tools intended to facilitate this collaboration.</p><p style='text-indent:20px;'>Evidence from the project evaluation, including participant survey and interview data, is presented to document the degree to which the project was successful in engaging students in team-based data science, and how the project changed the students' perceptions of their technical and non-technical skills. We also examine opportunities for improvement and offer insight to other data science educators who may want to implement a similar team-based approach to data science projects at their own institutions.</p>
Our complex world requires multivariate reasoning to make sense of reality. Within this paper, we offer a sequence of activities designed to develop multivariate reasoning by explicitly connecting data and visualization. The activities were designed based on a hypothetical learning trajectory we conjectured for students with limited experience with multivariate visualizations. Drawing from evidence collected using these activities in a series of professional development sessions with in-service teachers, we find that the activities functioned as intended, and thus we promote these activities for developing students' multivariate reasoning at the secondary and post-secondary level. We detail specific challenges the teachers faced, and based on these results, offer our reflections and recommendations for curricula and teaching.
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