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Project-Based Learning with a Social Impact: Connecting Data Science Movements, Civic Statistics, and Service-Learning

In: Statistics for Empowerment and Social Engagement

Author

Listed:
  • Leid Zejnilović

    (Nova School of Business and Economics, Nova University of Lisbon)

  • Pedro Campos

    (LIAAD-INESC TEC and University of Porto)

Abstract

Ever since there has been an organized collection and use of data for informing decision making, there has been a debate about the extent to which these data have been put to the best use for improving social welfare in terms of general well-being of a community or an entire society. This chapter offers a contribution to that debate, showing how different facets of civic statistics can be translated into action that delivers social impact. We first introduce data movements and how they emerged as a response to the unmet need for data science services to scale social impact of nonprofit and governmental organizations. These movements focused on feasible hands-on projects which are simultaneously educational, impactful, and scalable. Their success is notable, and their operational model applicable in the context of formal educational organizations, as we show using two exemplary cases. The cases offer insights about how organizations can engage with society through civic action and applied data science to create new academic and training programs. Our intention is to share the lessons learned from the data movements and their interactions with educational institutions, also in the context of service-learning, to inspire others to create exciting, engaging educational programs with lasting social impact.

Suggested Citation

  • Leid Zejnilović & Pedro Campos, 2022. "Project-Based Learning with a Social Impact: Connecting Data Science Movements, Civic Statistics, and Service-Learning," Springer Books, in: Jim Ridgway (ed.), Statistics for Empowerment and Social Engagement, chapter 0, pages 537-562, Springer.
  • Handle: RePEc:spr:sprchp:978-3-031-20748-8_21
    DOI: 10.1007/978-3-031-20748-8_21
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