GSU Data Science for Public Service Consortium

The project supported the work of the Data Science for Public Service Consortium (DS4PS), faculty representing ten schools of public affairs, aiming to deepen institutional capacity to offer courses in the technical skills and ethical foundations needed to effectively harness the promise of PIT in the public and nonprofit sectors. The consortium built and piloted open-source data science curricula appropriate for graduate students in public affairs. This project made progress in formalizing the consortium to scale PIT educational opportunities in public affairs and build clear career pathways to the public sector. The primary goal of this project was to leverage existing data science curricula so that significant resources are not needed to create new degrees/specializations within schools of public affairs (e.g., mostly MPA/MPP programs). The DS4PS faculty identified a core set of knowledge and skills needed to teach public and nonprofit managers/analysts the data science life cycle and mapped them against courses currently offered in schools of public affairs. This exercise took place prior to and during a 2.5-day symposium hosted by the Andrew Young School of Policy Studies in August 2022. Resources developed for the symposium and a draft consortium agreement were taken back to attendees’ institutions to gauge support for sharing and/or expanding curricula within their degree programs. In addition, resources were shared at the national conference for Schools of public affairs (NASPAA) in October 2022 and again at the National Conference for policy analysis and Management (APPAM) in November 2022. This grant supported research, planning, and travel for participants in the summer symposium. It also supported course template and website development to share the DS4PS curricula to schools of public affairs for use in existing courses or to initiate discussions among their faculty to adopt courses as they prepare future public and nonprofit leaders to manage data projects. The work followed this timeline: Jan – May 2022: Identification of courses/degrees in data science offered among top 30 schools of public affairs; list of symposium invitees developed based on schools offering data science courses/degrees May 2022: Data science courses mapped against the data project life cycle; symposium planning; participant RSVP and travel scheduling Aug 2022: DS4PS Symposium Sep-Oct 2022: Finalize sessions & meetup for NASPAA Annual Conference in Chicago; Revise course template for sample course Nov-Dec 2022: Meetup session at APPAM Fall Conference; Finalize course template and content for sample course Jan-Apr 2023: Test and review of course template; collect syllabi for course map; create website resources (ongoing)