Work

Who Plays Which Role When? Communication Role Dynamics for Peer Recognition and Team Performance Prediction

Year: 2026

Type: conference-paper

Abstract: Team roles offer an interpretable lens on collaboration, yet computational studies of roles often rely on domain-specific personas or datadriven clustering rather than theory-grounded taxonomies.We operationalize a taxonomy of eight communication roles grounded in education literature and annotate a corpus of 6,307 Slack messages from 55 students across 18 teams in a semester-long computer science course project.We evaluate whether LLMs can approximate expert labels, enabling scalable, taxonomy-driven role annotation.Using these role labels, we characterize role dynamics over teams' lifecycles, finding that different roles peak at different moments and that students enact a more diverse set of roles as projects progress.To evaluate the utility of our role constructs, we use them to predict peer recognition, outperforming lexical, conversational, and LLM-prompting baselines.To assess generalizability beyond the educational context, we apply the same role constructs to a public dataset (DeliData) to predict team performance improvement after deliberation, again exceeding prior performance.

Source: Proceedings of the conference - Association for Computational Linguistics. Meeting

DOI: 10.18653/v1/2026.acl-long.1930

Authors: Yifan Song, Wenxuan Wendy Shi, Brian Bailey, Tal August

Institutions: University of Illinois Urbana-Champaign, California State Polytechnic University

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

Funder: University of Illinois at Urbana-Champaign