From Discourse to Dynamics: Understanding Team Interactions Through Temporally Sensitive NLP

Collaborative Problem Solving (CPS) is a vital 21st-century skill that integrates social and cognitive processes to achieve shared goals. Despite its importance, understanding how communication dynamics shape individual learning outcomes in CPS tasks remains a challenge, particularly in virtual settings. To address this gap, this study analyzes discourse patterns using Group Communication Analysis (GCA), a temporally sensitive computational methodology for quantifying team interactions. Our work takes a novel approach by identifying discourse patterns associated with student performance. We examined the interaction patterns of 279 undergraduate students as they engaged in a virtual physics learning game, using GCA measures such as participation, internal cohesion, responsivity, social impact, newness, and communication density. Our findings suggest that students who introduced more novel contributions (i.e., newness), established common ground (i.e., overall responsivity) and engaged in denser communication showed significantly greater improvements in their post-test scores. These results provide valuable insights into optimizing virtual collaboration in educational settings, highlighting the role of novel information exchange between learners. This study emphasizes the importance of examining individual contributions and group dynamics, and proposes future research directions to the EDM community.