Retrieval-augmented generation for educational application: A systematic survey

Advancements in large language models (LLMs) have transformed AI-driven education, enabling innovative applications across various learning and teaching domains. However, LLMs still face several challenges, including hallucination and static internal knowledge, which hinder their reliability in educ...

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Bibliographic Details
Main Authors: Zongxi Li, Zijian Wang, Weiming Wang, Kevin Hung, Haoran Xie, Fu Lee Wang
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Computers and Education: Artificial Intelligence
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666920X25000578
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