2026 ASEE Annual Conference & Exposition

Group activities in academia are often curated to prepare students for the multidisciplinary teams they will inevitably encounter in industry. However, whether in industry or in the classroom, the choice of group members can have significant effects on project outcomes. Understanding group dynamics and optimizing team formation can positively influence the overall objectives of the group activity, resulting in a more satisfying and productive experience for the team members themselves and the outcome of the project.

This study presents an innovative method that applies graph theory to assess group dynamics in a multidisciplinary engineering classroom. The preliminary data collected and presented in this paper are from first-year honors engineering classrooms in the fall 2025 quarter, with data collection continuing through each quarter of the first-year engineering program for the 2025-2026 academic year. Audio recordings from team activities, including in-class discussions, small group work, and project collaboration, will be used to generate weighted bidirectional graphs representing each instance of student interaction. By analyzing the generated graphs and associated metrics, connections to each participant’s communication tendencies will be determined. Through analysis of these graphs, effective group dynamics can be identified and utilized in the creation of more effective groupings.

This work-in-progress paper will detail the process of data analysis and graph generation using the preliminary data collected, and an exploration into the connections between graphs and team dynamics.This early-stage research provides a foundation for more in-depth analysis of team dynamics through the lens of graph theory, and has implications on potential optimal group formation for team activities.