ExpertAgent: Enhancing Personalized Education through Dynamic Planning and Retrieval-Augmented Long-Chain Reasoning
On the map: LLM reasoning → Reinforcement learning for reasoning
Abstract (arXiv)
The application of advanced generative artificial intelligence in education is often constrained by the lack of real-time adaptability, personalization, and reliability of the content. To address these challenges, we propose ExpertAgent - an intelligent agent framework designed for personalized education that provides reliable knowledge and enables highly adaptive learning experiences. Therefore, we developed ExpertAgent, an innovative learning agent that provides users with a proactive and personalized learning experience. ExpertAgent dynamic planning of the learning content and strategy based on a continuously updated student model. Therefore, overcoming the limitations of traditional static learning content to provide optimized teaching strategies and learning experience in real time. All instructional content is grounded in a validated curriculum repository, effectively reducing hallucination risks in large language models and improving reliability and trustworthiness.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Reinforcement learning for reasoning, one of 17 directions in LLM reasoning. Builds on 6 of its 9 references that are in the map. First posted on arXiv 8 Oct 2025.
Builds on
6 of 9 references.
References · 6
- 2025LLM Agents for Education: Advances and Applicationscited by 59
- 2024EduAgent: Generative Student Agents in Learningcited by 42
- 2024AI Agent for Education: von Neumann Multi-Agent System Frameworkcited by 12
- 2024Transforming Teachers' Roles and Agencies in the Era of Generative AI: Perceptions, Acceptance, Knowledge, and Practicescited by 8
- 2024AI Agents and Education: Simulated Practice at Scalecited by 5
- 2022Equity and Fairness of Bayesian Knowledge Tracingcited by 2
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- 2026DeepTutor: Towards Agentic Personalized Tutoring
- 2025Instructional Agents: Reducing Teaching Faculty Workload through Multi-Agent Instructional Design
- 2025LLM-powered Multi-agent Framework for Goal-oriented Learning in Intelligent Tutoring System
- 2025EduPlanner: LLM-Based Multi-Agent Systems for Customized and Intelligent Instructional Design
- 2025Agentic Workflow for Education: Concepts and Applications