Year: 2025
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Chu, Zhendong, Wang, Shen, Xie, Jian, Zhu, Tinghui, Yan, Yibo, Ye, Jinheng, Zhong, Aoxiao, Hu, Xuming, Liang, Jing, Yu, Philip S., Wen, Qingsong
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W6979225770
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