JDS Journal of Data Science 1683-86021680-743X1680-743X School of Statistics, Renmin University of China JDS1129 10.6339/24-JDS1129 Education in Data Science Interdisciplinary Approaches to Teaching Communication and Ethics in Data Science: A Case Study ThatcherScottthatcher@truman.edu1∗ AlbertsK. Scott1 BeregovskaTetyana1 Department of Statistics, Truman State University, Kirksville, Missouri, U.S.A. Corresponding author. Email: thatcher@truman.edu. 20242942024222333351 Supplementary Material

The following files are included in the supplementary material:

Signature assignment in Narrative, Argument and Persuasion

Signature assignment on algorithmic bias in bail risk assessment

Algorithmic bias data set, modified from the original Pro Publica data set

Data visualization deconstruction assignment

SVG file containing components of Image 1 for the deconstruction assignment

SVG file containing components of Image 2 for the deconstruction assignment

Assignment using ggplot to recreate a historic data visualization by William Playfair

Data set of wheat and wages for use with the Playfair reconstruction

Data set of British monarchs for use with the Playfair reconstruction

182023442024 2024 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.2024 Open access article under the CC BY license.

By its nature, data science uses ideas and methodologies from computer science and statistics, along with field-specific knowledge, to describe, learn and predict. Recently, storytelling has been highlighted as an important extension of more traditional data science skills such as coding and modeling. Three courses in our new Master in Data Science and Analytic Storytelling program were designed to include interdisciplinary modules, mainly taught by faculty in storytelling-related disciplines, such as Communication and Art & Design. These courses were PDAT 622: Narrative, Argument, and Persuasion in Data Science; PDAT 624: Principles of Design in Data Visualization; and PDAT 625: Big Data Ethics and Security.

Our first cohort serves as a natural case study, allowing us to reflectively analyze our materials and an informal student survey to explore the effects of interdisciplinarity in these novel courses. Results of the student survey show that students generally found value in these interdisciplinary course components, especially in course “signature assignments,” which allow students to actively engage with course content while reinforcing technical skills from previous courses. Examples of these signature assignments are presented in this paper’s supplementary materials.

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