How Generative AI Affects Team Communication in Secondary Education: A Qualitative Investigation. - Hu, Wenjie; Chan, Cecilia Ka Yuk (Journal of Computer Assisted Learning, 2026)
Background: The integration of Generative AI (GenAI) into collaborative learning in secondary education has created new possibilities for this pedagogical approach. It has also raised concerns about its impact on team communication, particularly, for adolescent learners whose collaborative competencies are still developing. Current research offers limited understanding of how GenAI shapes team communication in educational settings. Objectives: This study explores how GenAI influences team communication during group tasks and identifies key factors shaping these dynamics in secondary education. Methods: A mixed‐methods design was employed with 24 secondary students (Grades 9–12) from two Hong Kong secondary schools. Data collection included written reflections from all participants and semistructured interviews with 10 students. Thematic analysis addressed GenAI's impacts on communication frequency, timeliness and quality (RQ1), while activity theory guided analysis of influencing factors (RQ2). Results and Conclusions: Findings underscore GenAI's dual role as both a facilitator and a potential disruptor of team interaction in secondary education. First, the introduction of GenAI tools improves communication quality by fostering deeper understanding, generating new ideas and resolving disagreements. However, generative AI tools also significantly reduce communication frequency among team members and may introduce delays in team exchanges. Moreover, this study identifies six factors influencing the use of GenAI in team communication as perceived by students, including the perceived value of discussions, task interdependence, team familiarity, attitudes towards AI, guidelines for AI use and role clarity. Lay Summary: What is currently known about this topic? ○GenAI is increasingly used in secondary education, yet concerns persist about its potential disruption to team communication.○Effective team communication remains critical for successful collaborative learning outcomes.What does this paper add? ○Reveals GenAI's dual role as both a facilitator and a disruptor of team communication.○Identifies six student‐perceived factors influencing the use of GenAI in team communication.Implications for practice or policy ○Develop clear guidelines that specify appropriate contexts and boundaries for GenAI use in collaborative learning.○Incorporate socioemotional team‐building activities (e.g., icebreakers) to strengthen team familiarity and trust.○Maximise task interdependence in group design to ensure students have meaningful opportunities for direct communication.