Closing the Gap: Can Novice Statistics and Data Science Students Collaborate as Effectively as an Expert?

The Attitude-Structure-Content-Communication-Relationship (ASCCR) framework was developed recently to teach collaboration skills to statisticians and data scientists. However, researchers have not yet systematically evaluated its effectiveness in real-world settings. To address this gap, we evaluated the performances of novice undergraduate and graduate students in initial collaboration meetings with real domain experts and compared them to an expert collaborator. Using video recordings, rubric scores, and domain expert feedback surveys, we found that novices performed surprisingly well compared to the expert. Specifically, novices scored nearly as well as the expert on the Attitude, Structure, and Relationship components of the ASCCR framework. Although novices initially underperformed on the Content and Communication aspects, they ultimately closed the gap. By the end of the collaboration projects, the novices had higher overall domain expert feedback scores than the expert. The primary implication of our study is that novices can become effective collaborators in a very short time. Finally, we discuss the practical implications of our findings and provide recommendations for integrating the ASCCR framework into statistics and data science collaboration, consulting, and capstone courses.