Using Team-Based Learning to Teach Data Science

ABSTRACT

Data science is collaborative and its students should learn teamwork and collaboration. Yet it can be a challenge to fit the teaching of such skills into the data science curriculum. Team-Based Learning (TBL) is a pedagogical strategy that can help educators teach data science better by flipping the classroom to employ small-group collaborative learning to actively engage students in doing data science. A consequence of this teaching method is helping students achieve the workforce-relevant data science learning goals of effective communication, teamwork, and collaboration. We describe the essential elements of TBL: accountability structures and feedback mechanisms to support students collaborating within permanent teams on well-designed application exercises to do data science. The results of our case study of using TBL to teach a modern, introductory data science course indicate that the course effectively taught reproducible data science workflows, beginning R programming, and communication and collaboration. Students also reported much room for improvement in their learning of statistical thinking and advanced R concepts. To help the data science education community adopt this appealing pedagogical strategy, we outline steps for deciding on using TBL, preparing and planning for it, and overcoming potential pitfalls when using TBL to teach data science.

KEYWORDS:

• Collaboration
• Cooperative learning
• R programming
• Small-group learning
• Statistical thinking
• Tidyverse

Acknowledgments

The author thanks his original TBL mentors Jarad Niemi and Sandra Stinnett and his students. He appreciates the work of Sebastian Kopf and Johnny Tamanaha in developing the tbltools package, Ethan Schacht for a preliminary analysis of the case study data, and his colleagues Nathan Pieplow and David Glimp as well as two editors and two anonymous reviewers for their helpful comments on the manuscript.

Additional information

Funding

This work was partially funded by NSF Division of Undergraduate Education grant #2044384 for IUSE: Collaborative Data Science Education: Statistics With Integration of Technology, Computing, and the Humanities (CODE:SWITCH).