Journal ArticleMerryQuery: A Trustworthy LLM-Powered Tool Providing Personalized Support for Educators and StudentsTabarsi, Benyamin; Basarkar, Aditya; Liu, Xukun; Xu, Dongkuan DK; Barnes, Tiffany<p>The potential of Large Language Models (LLMs) in education is not trivial, but concerns about academic misconduct, misinformation, and overreliance limit their adoption. To address these issues, we introduce MerryQuery, an AI-powered educational assistant using Retrieval-Augmented Generation (RAG), to provide contextually relevant, course-specific responses. MerryQuery features guided dialogues and source citation to ensure trust and improve student learning. Additionally, it enables instructors to monitor student interactions, customize response granularity, and input multimodal materials without compromising data fidelity. By meeting both student and instructor needs, MerryQuery offers a responsible way to integrate LLMs into educational settings.</p>The Association for the Advancement of Artificial Intelligence2025-04-1110644056Proceedings of the AAAI Conference on Artificial Intelligence392829700 to 297022159-5399https://doi.org/10.1609/aaai.v39i28.353721917885National Science Foundation