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Keeping the human in the data scientist: Shaping human‐centered data science education
Author(s) -
Anderson Theresa Dirndorfer,
Parker Nicola
Publication year - 2019
Publication title -
proceedings of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.193
H-Index - 14
ISSN - 2373-9231
DOI - 10.1002/pra2.103
Subject(s) - foregrounding , curriculum , nature versus nurture , session (web analytics) , computer science , relation (database) , engineering ethics , philosophy of science , data science , analytics , psychology , sociology , pedagogy , epistemology , engineering , philosophy , linguistics , database , world wide web , anthropology
Human‐centered approaches are still relatively novel for data science practice, where data‐driven analytics are often framed as ways to supersede human judgments. This poster presents core design principles devised by the authors to build a data science curriculum foregrounding ethics and valuing creative human capacities alongside strong data analytic skills. The curriculum design transforms human‐centered principles into practice. The poster visually illustrates the trajectory of these principles in relation to three specific graduate attributes, using a selection of deep dives into the learning design. To illustrate the specific power information theory and practice has to shape data science training, the poster uses evocative quotes from information science theorists and displays how their work significantly influenced the overall philosophy of the program, student activities and assessments. Using ‘gamestorming’ techniques during the poster session, the audience is invited to contribute further insights about ways to nurture the deeply human capacities of the data scientists we train.