教育中的LLM代理：进展与应用
LLM Agents for Education: Advances and Applications
AI总结：
本文综述了LLM代理在教育中的应用进展，探讨了其技术实现、挑战及在不同教育领域的应用。
摘要：
大型语言模型（LLM）代理正在通过自动化复杂的教学任务并增强教学和学习过程来改变教育领域。在本文的综述中，我们系统地回顾了最近将LLM代理应用于教育环境中的关键挑战，如反馈评论生成、课程设计等。我们分析了使这些代理能够运作的技术，包括代表性数据集、基准测试和算法框架。此外，我们还突出了在教育环境中部署LLM代理的关键挑战，包括伦理问题、幻觉和过度依赖，以及与现有教育生态系统整合的问题。除了核心技术关注点外，我们在附录A中还包含了一个关于领域特定教育代理的全面概述，涵盖科学学习、语言学习和专业发展等领域。
英文摘要：
Large Language Model (LLM) agents are transforming education by automating complex pedagogical tasks and enhancing both teaching and learning processes. In this survey, we present a systematic review of recent advances in applying LLM agents to address key challenges in educational settings, such as feedback comment generation, curriculum design, etc. We analyze the technologies enabling these agents, including representative datasets, benchmarks, and algorithmic frameworks. Additionally, we highlight key challenges in deploying LLM agents in educational settings, including ethical issues, hallucination and overreliance, and integration with existing educational ecosystems. Beyond the core technical focus, we include in Appendix A a comprehensive overview of domain-specific educational agents, covering areas such as science learning, language learning, and professional development.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
