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(2025): YY2025
Pub. online: 14 January 2025
Type: Article
Open Access
Open Access
Published
14 January 2025
14 January 2025
Abstract
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.