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Re-Shape: A Method to Teach Data Ethics for Data Science Education

Shapiro, Benjamin R.
Meng, Amanda
O'Donnell, Cody
Lou, Charlette
Zhao, Edwin
Dankwa, Bianca
Hostetler, Andrew
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Abstract

Data has become central to the technologies and services that human-computer interaction (HCI) designers make, and the ethical use of data in and through these technologies should be given critical attention throughout the design process. However, there is little research on ethics education in computer science that explicitly addresses data ethics. We present and analyze Re-Shape, a method to teach students about the ethical implications of data collection and use. Re-Shape, as part of an educational environment, builds upon the idea of cultivating care and allows students to collect, process, and visualizetheir physical movement data in ways that support critical reflection and coordinated classroom activities about data, data privacy, and human-centered systems for data science. We also use a case study of Re-Shape in an undergraduate computer science course to explore prospects and limitations of instructional designs and educational technology such as Re-Shape that leverage personal data to teach data ethics.

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<p>Originally published on ACM (Association of Computing Machinery):</p> <p>Ben Rydal Shapiro, Amanda Meng, Cody O'Donnell, Charlotte Lou, Edwin Zhao, Bianca Dankwa and Andrew Hostetler. 2020. Re-Shape: A Method to Teach Data Ethics for Data Science Education. In <em>Proceedings of CHI '20: CHI Conference on Human Factors in Computing Systems (CHI '20), April 25-30, 2020, Honolulu, HI, USA</em>. ACM, New York, NY, USA Pages 13, <a href="https://doi.org/10.1145/3313831.3376251">https://doi.org/10.1145/3313831.3376251</a></p> <p>https://dl.acm.org/doi/fullHtml/10.1145/3313831.3376251</p>
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2020-01-01
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Research Projects
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Data ethics, care ethics, data science education, information visualization, data literacy, data privacy, computer science education, re-shape, interaction geography slicer
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