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arXiv · 2609.35776

Teachers' perspective on AI-based Multi-Agent Simulation Design to Combat School Bullying

Jiaju Lin·Ellen Wenting Zou·Feiwen Xiao·Huanying Song
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Abstract

Bullying in schools profoundly affects the mental and physical health of teenagers. Although existing in-person and digital interventions provide some benefits, they often fall short in addressing the complex social dynamics of bullying. In this study, we collaborated with K-12 teachers to co-design a multi-agent anti-bullying system powered by large language models (LLMs). This system simulates authentic scenarios, enabling students to develop anti-bully skills. The research identifies key design parameters for an LLM-driven multi-agent simulation system, offering valuable insights for creating more effective and scalable anti-bullying tools that could significantly reduce bullying in schools} \keywords{anti-bullying interventions, multi-agent system, generative AI, co-design, bystander presence

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Jiaju Lin, Ellen Wenting Zou, Feiwen Xiao, Huanying Song. 2026-08-01. Teachers' perspective on AI-based Multi-Agent Simulation Design to Combat School Bullying. https://arxiv.org/abs/2609.35776

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