{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T14:08:10Z","timestamp":1775138890346,"version":"3.50.1"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032000552","type":"print"},{"value":"9783032000569","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>Massive Open Online Courses (MOOCs) lack direct interaction between learners and instructors, making it challenging for learners to understand new knowledge concepts. Recently, learners have increasingly used Large Language Models (LLMs)\u00a0to support them in acquiring new knowledge. However, LLMs are prone\u00a0to hallucinations which limits their reliability. Retrieval-Augmented Generation (RAG) addresses this issue by retrieving relevant documents before generating a response. However, the application\u00a0of RAG across different MOOCs is limited by unstructured learning material. Furthermore, current RAG systems do not actively\u00a0guide learners toward their learning needs. To address these challenges, we propose a Graph RAG pipeline that leverages Educational Knowledge Graphs (EduKGs) and Personal Knowledge Graphs (PKGs) to\u00a0guide learners to understand knowledge concepts in the MOOC platform CourseMapper. Specifically, we implement (1) a PKG-based Question Generation method to recommend personalized questions for learners in context, and (2) an EduKG-based Question Answering method\u00a0that leverages the relationships between knowledge concepts in the\u00a0EduKG to answer learner selected questions. To evaluate both methods,\u00a0we conducted a study with 3 expert instructors on 3 different MOOCs\u00a0in the MOOC platform CourseMapper. The results of the evaluation\u00a0show the potential of Graph RAG to empower learners to understand\u00a0new knowledge concepts in a personalized learning experience.<\/jats:p>","DOI":"10.1007\/978-3-032-00056-9_10","type":"book-chapter","created":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T22:27:01Z","timestamp":1759271221000},"page":"108-118","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Leveraging Graph Retrieval-Augmented Generation to\u00a0Support Learners\u2019 Understanding of\u00a0Knowledge Concepts in\u00a0MOOCs"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-9692-7540","authenticated-orcid":false,"given":"Mohamed","family":"Abdelmagied","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1311-7852","authenticated-orcid":false,"given":"Mohamed Amine","family":"Chatti","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4591-9742","authenticated-orcid":false,"given":"Shoeb","family":"Joarder","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2691-0267","authenticated-orcid":false,"given":"Qurat Ul","family":"Ain","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2192-028X","authenticated-orcid":false,"given":"Rawaa","family":"Alatrash","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,1]]},"reference":[{"key":"10_CR1","doi-asserted-by":"crossref","unstructured":"Abu-Rasheed, H., et al.: LLM-assisted knowledge graph completion for curriculum and domain modelling in personalized higher education recommendations. arXiv preprint arXiv:2501.12300 (2025)","DOI":"10.1109\/EDUCON62633.2025.11016377"},{"issue":"10","key":"10_CR2","doi-asserted-by":"publisher","first-page":"526","DOI":"10.3390\/info14100526","volume":"14","author":"QU Ain","year":"2023","unstructured":"Ain, Q.U., Chatti, M.A., Bakar, K.G.C., Joarder, S., Alatrash, R.: Automatic construction of educational knowledge graphs: a word embedding-based approach. 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In: Proceedings of the 14th Learning Analytics and Knowledge Conference, pp. 273\u2013283 (2024)","DOI":"10.1145\/3636555.3636881"},{"key":"10_CR5","unstructured":"Dan, Y., et\u00a0al.: EduChat: a large-scale language model-based chatbot system for intelligent education. arXiv preprint arXiv:2308.02773 (2023)"},{"key":"10_CR6","doi-asserted-by":"crossref","unstructured":"Fu, W., Wei, B., Hu, J., Cai, Z., Liu, J.: Qgeval: benchmarking multi-dimensional evaluation for question generation. arXiv preprint arXiv:2406.05707 (2024)","DOI":"10.18653\/v1\/2024.emnlp-main.658"},{"key":"10_CR7","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1016\/j.susoc.2022.05.004","volume":"3","author":"A Haleem","year":"2022","unstructured":"Haleem, A., Javaid, M., Qadri, M.A., Suman, R.: Understanding the role of digital technologies in education: A review. Sustain. Oper. Comput. 3, 275\u2013285 (2022)","journal-title":"Sustain. Oper. 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