91��Ƭ��

The ASSETT (Arts & Sciences Support of Education Through Technology) Innovation Incubator is thrilled to announce that the Inclusive Data Science team was recently awarded a $300,000 grant from the National Science Foundation Division of Undergraduate Education for their project, CODE:SWITCH (Collaborative Data Science Education: Statistics With Integration of Technology, Computing, and the Humanities) which aims to radically rethink undergraduate data science education. The project’s goal is to develop and assess new pedagogical approaches to teaching data science that effectively integrate perspectives of both STEM and humanities disciplines. The awarded team includes Principal Investigator (PI) Eric Vance (Applied Math), co-PIs  David Glimp (English), Vilja Hulden (History), Nathan Pieplow (Program for Writing & Rhetoric), and Jessica Alzen (Center for Assessment Design Research and Evaluation), and Senior Personnel Jane Garrity (English) and Brett Melbourne (Evolutionary Biology).  

This fall 2021, the team launched a new, team taught introductory course, Interdisciplinary Data Science for All (AHUM 1825), fully enrolled with 66 undergraduate students. In this course, students are learning to analyze not just numbers, but their human contexts and consequences; to prevent intentional or unintentional misuse of data science; and to communicate the findings of data analysis effectively — a set of competencies known as “data acumen.” The course uses real-world social issues to teach important statistics and coding skills alongside ways of thinking from the humanities, including careful textual analysis, rigorous attention to the kinds of categories people use to think about the world, close scrutiny of data sources, critical awareness of the harms and benefits of data collection and analysis, and assessment of the rhetorical aims and strategies of those who use data in politics and policymaking.  The course provides STEM majors with qualitative reasoning skills that are traditionally taught in the humanities, provides future humanities majors with an on-ramp to further study of data science, and provides all students with critical, statistical and computational skills they can apply in future courses and in the workforce. 

NSF funds will enable the team to study the effectiveness of the new course to determine how its educational model can be improved, adapted, and ultimately implemented at other colleges and universities. By crafting a more inclusive and human-centered approach to teaching the foundations of data science, and by developing a new collaborative model of data science education that can be adapted nationwide, this research team hopes to positively impact STEM education, leading to a more diverse, creative, and innovative national workforce and a more STEM-literate public.