Using Team-Based Learning to Teach Data Science. Issue 3 (2nd September 2021)

• Record Type: Journal Article
• Authors: Vance, Eric A.
• Is Part Of: Journal of Statistics and Data Science Education. Volume 29:Issue 3(2021)
• Page Start: 277
• Page End: 296
• Publication Date: 2021-09-02
• Subjects: Collaboration -- Cooperative learning -- R programming -- Small-group learning -- Statistical thinking -- Tidyverse
• DOI: Https://www.tandfonline.com/doi/10.1080/26939169.2021.1971587
• Languages: English
• ISSNs: 2693-9169

Abstract

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.