Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/47602
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dc.contributor.authorTHYS, Jarne-
dc.contributor.authorVANBRABANT, Sebe-
dc.contributor.authorVANACKEN, Davy-
dc.contributor.authorROVELO RUIZ, Gustavo-
dc.date.accessioned2025-10-27T10:09:10Z-
dc.date.available2025-10-27T10:09:10Z-
dc.date.issued2025-
dc.date.submitted2025-10-07T08:58:13Z-
dc.identifier.citationRuskov, Martin; Ognibene, Dimitri; Hernández-Leo, Davinia; Taibi, Davide; Dimitriadis, Yannis; Fulantelli, Giovanni; Handmann, Uwe; Zarifis, George; Wu, Yan; Ferri, Paolo Maria (Ed.). Artificial Intelligence in Education Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED, CEUR-WS.org, p. 32 -40 (Art N° 4)-
dc.identifier.isbn978-3-031-99266-7-
dc.identifier.issn1613-0073-
dc.identifier.urihttp://hdl.handle.net/1942/47602-
dc.description.abstractThe rise of AI, especially Large Language Models, presents challenges and opportunities to integrate such technology into the classroom. AI has the potential to revolutionize education by helping teaching staff with various tasks, such as personalizing their teaching methods, but it also raises concerns, for example, about the degradation of student-teacher interactions and user privacy. Based on interviews with teaching staff, this paper introduces INSIGHT, a proof of concept to combine various AI tools to assist teaching staff and students in the process of solving exercises. INSIGHT has a modular design that allows it to be integrated into various higher education courses. We analyze students' questions to an LLM by extracting keywords, which we use to dynamically build an FAQ from students' questions and provide new insights for the teaching staff to use for more personalized face-to-face support. Future work could build upon INSIGHT by using the collected data to provide adaptive learning and adjust content based on student progress and learning styles to offer a more interactive and inclusive learning experience.-
dc.description.sponsorshipThis work was supported by the Special Research Fund (BOF) of Hasselt University (BOF24OWB28 and BOF23OWB31). This research was made possible with support from the MAXVR-INFRA project, a scalable and flexible infrastructure that facilitates the transition to digital-physical work environments. The MAXVR-INFRA project is funded by the European Union- NextGenerationEU and the Flemish Government.-
dc.language.isoen-
dc.publisherCEUR-WS.org-
dc.relation.ispartofseriesCommunications in Computer and Information Science-
dc.rights© 2025 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).-
dc.subjectComputer Science - Human-Computer Interaction-
dc.subjectComputer Science - Human-Computer Interaction-
dc.subjectComputer Science - Artificial Intelligence-
dc.subject.otherAI Teaching Assistant-
dc.subject.otherTeaching Support-
dc.subject.otherStudent-Teacher Interaction-
dc.titleINSIGHT: Bridging the Student-Teacher Gap in Times of Large Language Models-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsRuskov, Martin-
local.bibliographicCitation.authorsOgnibene, Dimitri-
local.bibliographicCitation.authorsHernández-Leo, Davinia-
local.bibliographicCitation.authorsTaibi, Davide-
local.bibliographicCitation.authorsDimitriadis, Yannis-
local.bibliographicCitation.authorsFulantelli, Giovanni-
local.bibliographicCitation.authorsHandmann, Uwe-
local.bibliographicCitation.authorsZarifis, George-
local.bibliographicCitation.authorsWu, Yan-
local.bibliographicCitation.authorsFerri, Paolo Maria-
local.bibliographicCitation.conferencedate2025, July 22-
local.bibliographicCitation.conferencenameD-SAIL Workshop on Transformative Curriculum Design - Digitalisation, Sustainability, and AI Literacy for 21st Century Learning co-located with 26th International Conference on Artificial Intelligence in Education (AIED 2025)-
local.bibliographicCitation.conferenceplacePalermo, Italy-
dc.identifier.epage40-
dc.identifier.spage32-
dc.identifier.volume4051-
local.format.pages9-
local.bibliographicCitation.jcatC1-
local.publisher.placeAachen, Germany-
dc.relation.referencesAltinay, Z., Altinay, F., Dagli, G., Shadiev, R., & Othman, A. (2024). Factors Influencing AI Learning Motivation and Personalisation Among Pre-service Teachers in Higher Education. MIER Journal of Educational Studies Trends and Practices, 462–481. https://doi.org/10.52634/mier/2024/v14/i2/2714 Amanda Puteri, S., Saputri, Y., & Kurniati, Y. (2024). The Impact of Artificial Intelligence (AI) Technology on Students’ Social Relations. BICC Proceedings, 2, 153–158. https://doi.org/10.30983/bicc.v1i1.121 Artificial Analysis. (2025). Llama 3.2 Instruct 3B: Intelligence, Performance & Price Analysis. In Artificial Analysis. https://artificialanalysis.ai/models/llama-3-2-instruct-3b Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510 Gemma Team, Kamath, A., Ferret, J., Pathak, S., Vieillard, N., Merhej, R., Perrin, S., Matejovicova, T., Ramé, A., Rivière, M., Rouillard, L., Mesnard, T., Cideron, G., Grill, J., Ramos, S., Yvinec, E., Casbon, M., Pot, E., Penchev, I., … Hussenot, L. (2025). Gemma 3 Technical Report. arXiv. https://doi.org/10.48550/ARXIV.2503.19786 Grootendorst, M., Mishra, A., Matsak, A., OysterMax, Priyanshul Govil, Ogura, Y., Warmerdam, V. D., & Yusuke1997. (2023, September). MaartenGr/KeyBERT: V0.8. Zenodo. https://doi.org/10.5281/ZENODO.4461264 Huang, L. (2023). Ethics of Artificial Intelligence in Education: Student Privacy and Data Protection. Science Insights Education Frontiers, 16(2), 2577–2587. https://doi.org/10.15354/sief.23.re202 Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274 Nitze, A. (2024). Future-proofing Education: A Prototype for Simulating Oral Examinations Using Large Language Models. arXiv. https://doi.org/10.48550/ARXIV.2401.06160 OpenAI. (2024, November). Europe privacy policy. In OpenAI. https://web.archive.org/web/20250130122518/https://openai.com/policies/eu-privacy-policy/ Owan, V. J., Abang, K. B., Idika, D. O., Etta, E. O., & Bassey, B. A. (2023). Exploring the potential of artificial intelligence tools in educational measurement and assessment. Eurasia Journal of Mathematics, Science and Technology Education, 19(8), em2307. https://doi.org/10.29333/ejmste/13428 SBERT. (2025). Pretrained Models. In SBERT. https://www.sbert.net/docs/sentence_transformer/pretrained_models.html Shemshack, A., & Spector, J. M. (2020). A systematic literature review of personalized learning terms. Smart Learning Environments, 7(1), 33. https://doi.org/10.1186/s40561-020-00140-9 Taneja, K., Maiti, P., Kakar, S., Guruprasad, P., Rao, S., & Goel, A. K. (2024). Jill Watson: A Virtual Teaching Assistant Powered by ChatGPT. In A. M. Olney, I.-A. Chounta, Z. Liu, O. C. Santos, & I. I. Bittencourt (Eds.), Artificial Intelligence in Education (Vol. 14829, pp. 324–337). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-64302-6_23 Trotter, P., Vanderburg, M., & Vanderburg, R. (2024). AI-Assisted Pedagogies: Enhancing Mathematical Literacy and Open-Ended Problem-Solving with ChatGPT. ASCILITE Publications, 635–640. https://doi.org/10.14742/apubs.2024.1443 UHasselt. (2023). Algoritmen en datastructuren (4900). In UHasselt. https://studiegidswww.uhasselt.be/opleidingsonderdeel.aspx?a=2023&i=4900&n=4&t=01 Virginia Wesleyan University. (2025). Student Overview & Analytics in Learn Ultra. https://malboncenter.vwu.edu/services/academic-affairs-documentation/blackboard/blackboard-learn-ultra-documentation/student-overview-analytics-in-learn-ultra Wei, J., Wang, X., Schuurmans, D., Bosma, M., ichter, brian, Xia, F., Chi, E., Le, Q. V., & Zhou, D. (2022). Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), Advances in Neural Information Processing Systems (Vol. 35, pp. 24824–24837). Curran Associates, Inc. https://proceedings.neurips.cc/paper_files/paper/2022/file/9d5609613524ecf4f15af0f7b31abca4-Paper-Conference.pdf Wozniak, K. (2020). Personalized Learning for Adults: An Emerging Andragogy. In S. Yu, M. Ally, & A. Tsinakos (Eds.), Emerging Technologies and Pedagogies in the Curriculum (pp. 185–198). Springer Singapore. https://doi.org/10.1007/978-981-15-0618-5_11-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
local.bibliographicCitation.artnr4-
dc.identifier.arxivarXiv:2504.17677-
dc.identifier.eissn1865-0937-
local.provider.typeArXiv-
local.bibliographicCitation.btitleArtificial Intelligence in Education Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED-
local.uhasselt.internationalno-
item.contributorTHYS, Jarne-
item.contributorVANBRABANT, Sebe-
item.contributorVANACKEN, Davy-
item.contributorROVELO RUIZ, Gustavo-
item.fullcitationTHYS, Jarne; VANBRABANT, Sebe; VANACKEN, Davy & ROVELO RUIZ, Gustavo (2025) INSIGHT: Bridging the Student-Teacher Gap in Times of Large Language Models. In: Ruskov, Martin; Ognibene, Dimitri; Hernández-Leo, Davinia; Taibi, Davide; Dimitriadis, Yannis; Fulantelli, Giovanni; Handmann, Uwe; Zarifis, George; Wu, Yan; Ferri, Paolo Maria (Ed.). Artificial Intelligence in Education Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED, CEUR-WS.org, p. 32 -40 (Art N° 4).-
item.accessRightsOpen Access-
item.fulltextWith Fulltext-
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