Retrieval-Augmented Generation (RAG) Chatbots for Education: A Survey of Applications

Retrieval-Augmented Generation (RAG) overcomes the main barrier for the adoption of LLM-based chatbots in education: hallucinations. The uncomplicated architecture of RAG chatbots makes it relatively easy to implement chatbots that serve specific purposes and thus are capable of addressing various n...

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Main Authors: Jakub Swacha, Michał Gracel
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/15/8/4234
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author Jakub Swacha
Michał Gracel
author_facet Jakub Swacha
Michał Gracel
author_sort Jakub Swacha
collection DOAJ
description Retrieval-Augmented Generation (RAG) overcomes the main barrier for the adoption of LLM-based chatbots in education: hallucinations. The uncomplicated architecture of RAG chatbots makes it relatively easy to implement chatbots that serve specific purposes and thus are capable of addressing various needs in the educational domain. With five years having passed since the introduction of RAG, the time has come to check the progress attained in its adoption in education. This paper identifies 47 papers dedicated to RAG chatbots’ uses for various kinds of educational purposes, which are analyzed in terms of their character, the target of the support provided by the chatbots, the thematic scope of the knowledge accessible via the chatbots, the underlying large language model, and the character of their evaluation.
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spelling doaj-art-50c2a52d2ab84e4cb4c4feece3eb8a6c2025-08-20T02:17:19ZengMDPI AGApplied Sciences2076-34172025-04-01158423410.3390/app15084234Retrieval-Augmented Generation (RAG) Chatbots for Education: A Survey of ApplicationsJakub Swacha0Michał Gracel1Department of Information Technology in Management, University of Szczecin, 71-004 Szczecin, PolandDepartment of Information Technology in Management, University of Szczecin, 71-004 Szczecin, PolandRetrieval-Augmented Generation (RAG) overcomes the main barrier for the adoption of LLM-based chatbots in education: hallucinations. The uncomplicated architecture of RAG chatbots makes it relatively easy to implement chatbots that serve specific purposes and thus are capable of addressing various needs in the educational domain. With five years having passed since the introduction of RAG, the time has come to check the progress attained in its adoption in education. This paper identifies 47 papers dedicated to RAG chatbots’ uses for various kinds of educational purposes, which are analyzed in terms of their character, the target of the support provided by the chatbots, the thematic scope of the knowledge accessible via the chatbots, the underlying large language model, and the character of their evaluation.https://www.mdpi.com/2076-3417/15/8/4234RAG chatboteducational chatbotlarge language models in educationLLMs for educationAI teaching supportAI learning support
spellingShingle Jakub Swacha
Michał Gracel
Retrieval-Augmented Generation (RAG) Chatbots for Education: A Survey of Applications
Applied Sciences
RAG chatbot
educational chatbot
large language models in education
LLMs for education
AI teaching support
AI learning support
title Retrieval-Augmented Generation (RAG) Chatbots for Education: A Survey of Applications
title_full Retrieval-Augmented Generation (RAG) Chatbots for Education: A Survey of Applications
title_fullStr Retrieval-Augmented Generation (RAG) Chatbots for Education: A Survey of Applications
title_full_unstemmed Retrieval-Augmented Generation (RAG) Chatbots for Education: A Survey of Applications
title_short Retrieval-Augmented Generation (RAG) Chatbots for Education: A Survey of Applications
title_sort retrieval augmented generation rag chatbots for education a survey of applications
topic RAG chatbot
educational chatbot
large language models in education
LLMs for education
AI teaching support
AI learning support
url https://www.mdpi.com/2076-3417/15/8/4234
work_keys_str_mv AT jakubswacha retrievalaugmentedgenerationragchatbotsforeducationasurveyofapplications
AT michałgracel retrievalaugmentedgenerationragchatbotsforeducationasurveyofapplications