Laaroussi, YannisSwamy, VinitraMejia-Domenzain, PaolaVauthey, AdrienYazici, AybarsPerrot, MaximeKäser, Tanja2025-06-112025-06-112025-06-112025-06-22https://infoscience.epfl.ch/handle/20.500.14299/251244We present BloomTutor, an Intelligent Tutoring System (ITS) that integrates Retrieval-Augmented Generation (RAG) with Bloom's Taxonomy to support learners in exploring, revising, or querying specific topics within a predefined subject or course. Our system retrieves relevant course materials based on user queries, segments them into concise chunks, and generates questions aligned with cognitive levels. Learner responses guide real-time adjustments in question difficulty, enabling progression toward higher-order thinking or reinforcement of foundational concepts. Unlike most ITS that rely on fixed question banks, Bloom-Tutor generates context-specific questions in real time, allowing greater coverage and responsiveness to diverse learner queries and progress.enPersonalized EducationRetrieval-Augmented GenerationLarge Language ModelBloom's TaxonomyAdaptivitytext::conference output