Artificial intelligence-based chatbots improve the efficiency of course orientation among medical students: a cross-sectional study
Artificial intelligence-assisted information retrieval significantly improved students' ability to locate and understand key course content. Despite comparable time-on-task and navigation behaviours between groups, students using the ChatGPT-based chatbot achieved markedly higher test scores, likely due to the simplified and focused responses it provided. The absence of zero scores in the AI group and enhanced performance on logistical questions suggest that conversational interfaces may improve comprehension and retention of procedural information. These results highlight the potential of LLM-based tools to support more efficient onboarding in medical education, with a potential for broader applications across educational settings.
Authors
- Gergely H. Fodor (ORCID: https://orcid.org/0000-0002-4736-4966)
- Ferenc Rárosi (ORCID: https://orcid.org/0000-0002-1014-9242)
- József Tolnai (ORCID: https://orcid.org/0000-0002-7648-764X)
- Ferenc Peták (ORCID: https://orcid.org/0000-0001-6249-9327)
- Attila Nagy (ORCID: https://orcid.org/0000-0002-5921-8376)
Institutions
- University of Szeged (HU)
Publication Details
- Journal
- BMC Medical Education
- Published
- 2025-11-05
- DOI
- https://doi.org/10.1186/s12909-025-08146-y
- Citations
- 1
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- Hungarian Scientific Research Fund
- Nemzeti Kutatási Fejlesztési és Innovációs Hivatal
- Szegedi Tudományegyetem