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

2026-02-06

AI Summary

This study addresses the challenges teachers face in facilitating face-to-face small-group collaboration among students and explores the yet-unclear educational value of generative AI in this context. Through an exploratory qualitative investigation involving playtesting, surveys, and focus group interviews with 33 K–12 teachers, the research examines educators’ perceptions of Phoenix—a voice-based conversational AI agent designed to function as a “near-peer” collaborator. Findings reveal teachers’ mental models of collaborative AI and highlight key design tensions centered on autonomy, trust, anthropomorphism, and pedagogical alignment. While participants generally acknowledged Phoenix’s potential to enhance student engagement, they also expressed multiple concerns regarding its practical classroom implementation. These insights offer empirical grounding and novel perspectives for the design of AI systems that support group-based learning environments.

Technology Category

• Humans and AI: Human-AI Collaboration / Human-AI Teaming
• Philosophy and Ethics of AI: Artificial General Intelligence
• Multiagent Systems: Teamwork

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Search and Retrieval-Augmented AI: Agentic search

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.

Problem

• conversational AI
• group collaboration
• teacher perspectives
• AI in education
• peer interaction

Innovation

• conversational AI
• group collaboration
• teacher perspectives
• educational AI
• voice-based agent