Exploring Teachers' Perspectives on Using Conversational AI Agents for Group Collaboration

TL;DR

This paper investigates how K-12 teachers perceive a voice-based near-peer AI agent, Phoenix, as a mediator of face-to-face group collaboration. Using playtests, reflection surveys, and focus groups with 33 teachers, the study analyzes teachers' mental models of Phoenix, trust dynamics, and envisioned classroom roles. The findings reveal design tensions around agency, credibility, and anthropomorphism, and offer implications for integrating group-facing AI agents that scaffold meaningful collaboration and AI literacy. The work advances understanding of educators’ perspectives on AI-enabled peer interaction and informs design guidelines for future classroom CAs.

Abstract

Collaboration is a cornerstone of 21st-century learning, yet teachers continue to face challenges in supporting productive peer interaction. Emerging generative AI tools offer new possibilities for scaffolding collaboration, but their role in mediating in-person group work remains underexplored, especially from the perspective of educators. This paper presents findings from an exploratory qualitative study with 33 K12 teachers who interacted with Phoenix, a voice-based conversational agent designed to function as a near-peer in face-to-face group collaboration. Drawing on playtesting sessions, surveys, and focus groups, we examine how teachers perceived the agent's behavior, its influence on group dynamics, and its classroom potential. While many appreciated Phoenix's capacity to stimulate engagement, they also expressed concerns around autonomy, trust, anthropomorphism, and pedagogical alignment. We contribute empirical insights into teachers' mental models of AI, reveal core design tensions, and outline considerations for group-facing AI agents that support meaningful, collaborative learning.