LLMs in Problem-Based Learning: The Grounding Issue...24th International Conference of Informatics, Management and Technology in Healthcare (ICIMTH), July 3-5, 2026, Athens, Greece.
Large language models (LLMs) are increasingly used in medical education, including in problem-based learning (PBL). Their ability to summarize cases, generate differential diagnoses, and structure discussion raises the question of whether they might eventually replace PBL rather than merely support...
| Publicado en: | Studies in Health Technology & Informatics Vol. 338; pp. 698 - 703 |
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| Autor principal: | |
| Formato: | proceedings Journal Article |
| Publicado: |
Sage Publications Inc.
2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=195115710&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 195115710 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2026 vid: 338 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 195115710 195115710 195115710 10.3233/SHTI260935 195115710 ppf: 698 ppct: 5 formats: tig: atl: LLMs in Problem-Based Learning: The Grounding Issue...24th International Conference of Informatics, Management and Technology in Healthcare (ICIMTH), July 3-5, 2026, Athens, Greece. aug: au: SARIYAR, Murat affil: Bern University of Applied Sciences, IODA Institute, Bern, Switzerland sug: subj: Natural Language Processing Problem-Based Learning Kidney Neoplasms Education Chatbot Teaching Education, Medical Congresses and Conferences Greece Greece Human Judgment Uncertainty Decision Support Techniques Diagnosis, Differential Medical Informatics ab: Large language models (LLMs) are increasingly used in medical education, including in problem-based learning (PBL). Their ability to summarize cases, generate differential diagnoses, and structure discussion raises the question of whether they might eventually replace PBL rather than merely support it. This paper offers a conceptual analysis of that question, using a renal-tumor PBL case derived from recent ChatGPT-assisted teaching research as an illustrative use case. It distinguishes among semantic support, representational uncertainty, and situated uncertainty. LLMs can contribute substantially at the first two levels: they can reformulate cases, identify missing information, keep multiple diagnostic possibilities in play, and suggest coherent next steps. What they do not reproduce is the situated uncertainty through which PBL forms judgment in interaction with peers and tutors. More tools, retrieval, modalities, or sensor input may enrich representation, but they do not by themselves close this gap. The paper therefore argues that LLMs can augment PBL in important ways but do not replace its role in the formation of clinical judgment. pubtype: Academic Journal doctype: proceedings Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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