Addressing school bullying effectively and promptly is crucial for the mental health of students. This study examined the potential of large language models (LLMs) to empower students by discerning between bullying and joking in school peer interactions. We employed ChatGPT-4, Gemini 1.5 Pro, and Claude 3 Opus, evaluating their effectiveness through human review. Our results revealed that not all LLMs were suitable for an agentic approach, with ChatGPT-4 showing the most promise. We observed variations in LLM outputs, possibly influenced by political overcorrectness, context window limitations, and pre-existing bias in their training data. ChatGPT-4 excelled in context-specific accuracy after implementing the agentic approach, highlighting its potential to provide continuous, real-time support to vulnerable students. This study underlines the significant social impact of using agentic AI in educational settings, offering a new avenue for reducing the negative consequences of bullying and enhancing student well-being.

本研究针对学校中欺凌问题的紧迫性，探讨了大型语言模型（LLMs）如何帮助学生辨别同伴互动中的欺凌与玩笑。研究表明，ChatGPT-4在实施代理方法后，展现出在特定上下文中的准确性，能够为脆弱学生提供实时支持，从而在教育环境中有效减轻欺凌带来的负面影响。

AgentPeerTalk：通过代理人工智能驱动的同伴互动中欺凌与玩笑的辨别，赋能学生