LLM Agents for Education: Advances and Applications
On the map: LLM agents and tool use → Educational agents and math problem solving
Abstract (arXiv)
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.
Key facts. Cited by 59 papers in the map (data through 14 Oct 2026). Placed in Educational agents and math problem solving, one of 16 directions in LLM agents and tool use. Builds on 129 of its 256 references that are in the map. First posted on arXiv 14 Mar 2025.
Builds on
129 of 256 references.
Closest ancestors · 11
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Citing papers per year: 2025: 35; 2026: 24.
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