Training Interdisciplinary Data Science Collaborators: A Comparative Case Study


Tuesday, April 9th, 20244:00 pm – 4:30 pm ET

Presented by: Eric Vance (University of Colorado Boulder) and Jessica Alzen (University of Colorado Boulder)


Abstract

Abstract: In this April edition of the JSDSE/CAUSE webinar series, we highlight the 2023 article: Training Interdisciplinary Data Science Collaborators: A Comparative Case Study.  The authors will discuss their work developing a method for teaching statistics and data science collaboration, a framework for identifying elements of effective collaboration, and a comparative case study to evaluate the collaboration skills of both a team of students and an experienced collaborator on two components of effective data science collaboration: structuring a collaboration meeting and communicating with a domain expert. Results show that the students could facilitate meetings and communicate comparably well to the experienced collaborator, but that the experienced collaborator was better able to facilitate meetings and communicate to develop strong relationships, an important element for high-quality and long-term collaboration. Further work is needed to generalize these findings to a larger population, but these results begin to inform the field regarding effective ways to teach specific data science collaboration skills.
 


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