Author(s):
Data science needs practitioners with keen data acumen. This means data science education needs a greater focus on ethical, contextual, and rhetorical concerns. Meanwhile, humanities education needs better integration with data science. Both areas want increased student enrollment. To meet these needs, we designed a new introductory data science course at the University of Colorado Boulder to be team-taught by faculty from the quantitative sciences and the humanities. We taught 56 students in Fall 2021, 80 students in Fall 2022, and 140 students in Fall 2023. Our guiding questions for this study are (1) How well does our innovative pedagogical approach cultivate students’ data acumen? (2) In what ways and to what degree does our introductory course change attitudes about STEM, data science, and the humanities? (3) How effectively do students achieve student learning outcomes (SLOs)? After three iterations of the course (2021-2023), we report the following outcomes. We have made the course more sustainable by scaling up the number of students to 180 and moving from interdisciplinary team teaching to a single instructor. We see satisfactory levels of achievement in both humanities and data science SLOs, with continued room for improvement. On the final exam in fall 2023, students averaged over 50% achievement on all SLOs assessed, and over 80% achievement on two STEM SLOs and two humanities SLOs. We are not yet satisfied with our success in recruiting and retaining students from underrepresented backgrounds. Our course attracts more STEM majors seeking to fulfill humanities credits than humanities majors seeking to fulfill quantitative reasoning credits. In terms of broader Impacts, by establishing a collaborative model for data science education that values the humanities, we aim to open pathways into data science for more and more diverse undergraduates, making them effective and ethical producers of data-driven inquiry and informed, reflective, critical consumers of data and research results. We are working to establish a model for greater collaboration between humanities programs and quantitative science programs. Our introductory course, AHUM 1825, does not substitute for a complete introductory course in data science, but it successfully attracts students who otherwise might not have taken data science at all. AHUM 1825 has proven popular among students and has spurred development of several humanities courses that incorporate aspects of data science, including digital humanities courses and writing courses in the interdisciplinary data science minor. We are beginning to see students from AHUM 1825 enroll in these subsequent courses, suggesting that we have succeeded in establishing alternate pipelines into data science and related fields.
Coauthors
Eric Vance, University of Colorado Boulder; Nathan Pieplow, University of Colorado Boulder; David Glimp, University of Colorado Boulder; Brett Melbourne, University of Colorado Boulder; Vilja Hulden, University of Colorado Boulder; Jane Garrity, University of Colorado Boulder; Estelle Lindrooth, University of Colorado Boulder; Michael Schneider, University of Colorado Boulder
