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

TL;DR

This study explores K12 teachers' perceptions of a voice-based AI agent called Phoenix, highlighting its potential to enhance collaboration and the challenges related to trust, autonomy, and pedagogical fit.

Contribution

It provides empirical insights into teachers' mental models of conversational AI agents in face-to-face learning environments and discusses design considerations.

Findings

Teachers appreciated Phoenix's engagement but raised concerns about trust and autonomy.

The study reveals teachers' perceptions of AI's role in supporting collaborative learning.

Design tensions include balancing engagement with pedagogical alignment.

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.