Proof of Concept: An Algorithm for Consideration of Students’ Personalities in Team Formation

Team-based pedagogy is common across engineering, especially in introductory courses and senior design projects. Although team-based learning provides students with many benefits, not all students benefit equally from it. Due to the fact that students of a team may come from vastly different backgrounds (academically and non-academically), faculty members find it difficult to predict barriers to team success. Better prediction of student and team outcomes would allow for better pedagogical decision-making in the formation and support of team-based learning. This methodological paper describes a dataset including student personality and team preference inputs, self-and-peer-assessments of teamwork, and perceptions of teamwork outcomes. We use student- and team-level inputs to consider students' likelihood of dominating group discussions. Using such information, we propose a method for clustering students for analysis with the aim of finding ways to group students into teams more effectively to help achieve their particular goals or alleviate their concerns.