CyberTraining: CIU: Preparing the Public Sector Research Workforce to Impact Communities through Data Science

The ability to share data among researchers, citizens, government agencies, and educators creates potential for new research collaborations with significant real-world impact. However, cities are often unprepared to use cyberinfrastructure to support research that would impact their citizens and communities, and researchers often do not have access to or awareness of the kinds of data and questions that are relevant for communities. This project develops innovative and scalable instructional materials, for both in-person and online courses, to increase data science literacy to meet the public sector's emerging needs for experts in computational and data science. The materials emphasize the types of data necessary for communities to make informed decisions (e.g., administrative data on land use, constituent service requests, and crime statistics) and applies them to pressing issues presented by community partners, providing a real-world context for learning. The project leverages the University of Michigan School of Information's Citizen Interaction Design program and the Summer Program in Quantitative Methods of Social Research at the Inter-university Consortium for Political and Social Research (ICPSR) to train undergraduate students, graduate students, and public sector researchers in collecting, extracting, cleaning, annotating, and analyzing data generated and used by government organizations. The project serves the national interest, as stated by NSF's mission: to promote the progress of science; to advance the national health, prosperity and welfare; by enabling cities to conduct research that improves their communities and making the instructional materials and data used in the courses available for use by other interested educators, communities, and citizens. 

The project addresses bottlenecks in scientific and engineering research workforce development by developing and offering three instructional activities: (a) a project-based course in which students work directly with Michigan communities to design cyberinfrastructure tools, and (b) two massive, open online courses (MOOCs) in which students learn the fundamentals of data science for work in the public sector. These courses provide scalable training and education programs to increase cyberinfrastructure-enabled research in the public sector that leverages administrative data. Course development occurs in collaboration between educators and community partners in cities throughout the Midwest, in order to ensure diversity of topics and audiences, timeliness, relevance, and direct application. This reliance on real data and immediate application to community issues is a novel approach in data science instruction. Despite being offered virtually, the MOOCs retain the pedagogical benefits of working on meaningful projects with real stakeholders. All three courses will be offered and evaluated at least once over the course of the project, and the course materials will be made publicly available through the University of Michigan?s School of Information, ICPSR, and other forums (e.g., the University's institutional repository, Deep Blue) for maximum impact. The long-term goals are to broaden engagement between researchers and communities to leverage advanced cyberinfrastructure to support public sector STEM research and to contribute to the infrastructure for online, dynamic, personalized lessons and certifications. Through partnership with the Midwest Big Data Hub, the project ensures that communities in the Midwest have access to resources for workforce development and opportunities to refine educational materials to serve their specific needs now and in the future.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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