Convergence HDR: Social Science Insights for 21st Century Data Science Education (SSI)

University Of California-Berkeley, Berkeley CA

Investigators

Abstract

A pair of workshops will be conducted to develop innovative ways of incorporating social science findings about the practice of data science and insights from educational research into data science curricula. The workshop series will develop elements of 21st-century data science education anchored in the doing of data science in disciplinary research settings. Workshop participants will form a community of practice with practicing data scientists, educators, and social scientists working together. This project promotes Convergence by integrating insights from social science research and education research in the context of addressing the problem of how to teach data science and develop the appropriate curricular materials. The first workshop is planned for 1.5 days with about 50 participants, and will strive to identify key insights from social science research and education research into the practice of data science, in the service of their translation into data science curriculum. It will draw on findings from a range of social science disciplines (such as science and technology studies, ethnographic observation of transdisciplinary collaboration, computer supported cooperative work, work on inclusion and diversity in teams, organizational / management theory, systems thinking in design, and the human/technology interface) and educational research and design together with disciplinary data science practitioners and educators. In panels and working sessions, the workshop will draw in participants to frame key themes associated with the doing of data science and develop ways of targeting these to curriculum design. The product from this workshop will be a publicly available white paper identifying core insights for the next stage of work. In the intervening period between the first and second workshops, the observations and insights from the first workshop will be recorded and refined for use by the second workshop. In the interest of cross-fertilization, the workshop organizers will also make contact with select industry practitioners to assess the importance of the identified concepts for data science translated to real world application. The second workshop will be for 1 day with about 30 participants. It will outline and construct implementable approaches for translating the key insights into data science curricula. Thematic sessions through the day will build on the taxonomy of key insights developed in the first workshop, and address substantive issues around practical implementation, and prototyping of new curricular forms. The products from this workshop will be a fleshed-out set of curricular elements (such as exercises, course modules, etc.) and best practices guidelines to be publicly disseminated. These workshops will spotlight the doing of data science as a key arena for collaboratively engaging data science educators and social scientists in curriculum design. This project reorients the transdisciplinary data science education agenda by focusing on practitioners and practice. The workshops will develop implementable, publicly available curricular elements and best practices for data science education oriented to the collaborative doing of data science, with attention to important issues such as diversity, inclusion, and societal and ethical context.