Navigating virtual teams in generative AI-led learning: The moderation of team perceived virtuality

Abstract This study advances the understanding of Artificial Intelligence (AI)’s role, particularly that of conversational agents like ChatGPT, in augmenting team-based knowledge acquisition in virtual learning settings. Drawing on human-AI teams and anthropomorphism theories and addressing the gap in the literature on human-AI collaboration within virtual teams, this study examines a multi-level, longitudinal model using a sample of 344 graduate students from 48 student project teams in online project-based learning environments. Our model investigates the direct and interactional effects of AI characteristics —autonomy and explainability— and team perceived virtuality (TPV) on the learners’ knowledge-updating process. Findings indicate that embedding AI in learning teams supports knowledge acquisition and learning intentions. The results reveal that while AI explainability significantly enhances knowledge update perceptions, AI autonomy alone does not directly influence knowledge acquisition. Instead, the positive effect of AI autonomy on knowledge updating is contingent upon a high TPV within the team. These findings offer new theoretical insights into AI’s empowering role in educational contexts and provide practical guidance for integrating AI into virtual team learning. This research underlines the importance of designing AI tools with a focus on explainability and leveraging the synergy between AI autonomy and TPV to maximize learning outcomes.