{"type":"ScholarlyArticle","title":"From Surface Learning to Deep Understanding: A Grounded AI Tutoring System for Moodle","authors":[{"name":"Anna Ostrowska","slug":"anna-ostrowska","given":"Anna","family":"Ostrowska","affiliation":""},{"name":"Michał Kukla","slug":"micha-kukla","given":"Michał","family":"Kukla","affiliation":""},{"name":"Gabriela Majstrak","slug":"gabriela-majstrak","given":"Gabriela","family":"Majstrak","affiliation":""},{"name":"Jan Opala","slug":"jan-opala","given":"Jan","family":"Opala","affiliation":""},{"name":"Sebastian Pergała","slug":"sebastian-perga-a","given":"Sebastian","family":"Pergała","affiliation":""},{"name":"Jan Skwarek","slug":"jan-skwarek","given":"Jan","family":"Skwarek","affiliation":""},{"name":"Anna Wróblewska","slug":"anna-wroblewska","given":"Anna","family":"Wróblewska","affiliation":""}],"abstract":"This demo paper describes the development of the AI Teaching & Learning Assistant, a modular Moodle plugin that leverages Retrieval-Augmented Generation (RAG) to deliver high-quality, highly\r\nselective answers strictly grounded in teachers’ materials. The system employs a dual-centric design, providing students with interactive, Socratic-based tutoring options and educators with a “human-in-the-loop” workspace for supervised content generation, e.g., quizzes, tasks, or short summaries. By grounding Large Language Model (LLM) responses in teacher-provided materials, the assistant addresses the risks of misinformation while encouraging deep conceptual mastery. Evaluation via the LLM-as-a-Judge framework and a preliminary user study confirms its effectiveness, achieving faithfulness scores up to 0.97 and a 4.00/5.00 recommendation rate.\r\n\r\nDemo Video:  https://tinyurl.com/4zz4bcjn","doi":"10.24963/ijcai.2026/984","url":"https://ijcai.org/proceedings/2026/984","pdf":"https://ijcai.org/proceedings/2026/0984.pdf","markdown":"https://ijcai.org/proceedings/2026/984.md","bibtex":"https://ijcai.org/proceedings/2026/bibtex/984","volume":{"slug":"2026","title":"Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2026","url":"https://ijcai.org/proceedings/2026/","year":2026,"location":"Bremen, Germany","dates":"15-21 August 2026","editors":"Diego Calvanese","isbn":"978-1-956792-09-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2026"},"section":"Demo Track","track":"Demo Track","number":984,"pages":{"first":8479,"last":8482},"keywords":["AI: Multidisciplinary Topics and Applications","AI: Natural Language Processing","AI: Search","AI: Humans and AI"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}