Designing AI Peers for Collaborative Mathematical Problem Solving with Middle School Students: A Participatory Design Study

2026-01-25

AI Summary

This study addresses the challenge that middle school students often struggle in collaborative mathematical problem solving due to insufficient teacher support, while existing AI systems predominantly focus on one-on-one tutoring and offer limited assistance in collaborative learning contexts. Through a participatory design approach, 24 middle school students engaged with an interactive generative AI probe to complete mathematics tasks and co-design their ideal AI peer. Findings reveal that students prefer an AI that assumes a “humble yet competent” role, providing progressive scaffolding—such as hints and verification—under student direction, and exhibiting a friendly, professional persona rather than exaggerated anthropomorphism. The study distills design principles for AI peers tailored to collaborative mathematics learning in middle school, offering theoretical and practical insights into the role configuration and interaction mechanisms of educational AI.

Technology Category

• Humans and AI: Learning Human Values and Preferences
• Intelligent Robots: Embodied AI
• Multiagent Systems: Teamwork

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

Collaborative problem solving (CPS) is a fundamental practice in middle-school mathematics education; however, student groups frequently stall or struggle without ongoing teacher support. Recent work has explored how Generative AI tools can be designed to support one-on-one tutoring, but little is known about how AI can be designed as peer learning partners in collaborative learning contexts. We conducted a participatory design study with 24 middle school students, who first engaged in mathematics CPS tasks with AI peers in a technology probe, and then collaboratively designed their ideal AI peer. Our findings reveal that students envision an AI peer as competent in mathematics yet explicitly deferential, providing progressive scaffolds such as hints and checks under clear student control. Students preferred a tone of friendly expertise over exaggerated personas. We also discuss design recommendations and implications for AI peers in middle school mathematics CPS.

Problem

• collaborative problem solving
• AI peer
• middle school mathematics
• participatory design
• Generative AI

Innovation

• participatory design
• AI peer
• collaborative problem solving
• scaffolding
• generative AI