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

Institutions

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

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial intelligence-based chatbots improve the efficiency of course orientation among medical students: a cross-sectional study

Gergely H. Fodor, Ferenc Rárosi, József Tolnai, Ferenc Peták et al.
1 citations
BMC Medical Education
AI in Service Interactions
2.48
article

Artificial intelligence-based chatbots improve the efficiency of course orientation among medical students: a cross-sectional study

Gergely H. Fodor, Ferenc Rárosi, József Tolnai, Ferenc Peták, Attila Nagy
article en
1 citations

Abstract

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.

BMC Medical EducationVol. 25(1)
University of Szeged (HU)
Hungarian Scientific Research Fund, Nemzeti Kutatási Fejlesztési és Innovációs Hivatal, Szegedi Tudományegyetem
Openalex Percentile: Top 8%
AI in Service Interactions
2.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Artificial intelligence-based chatbots improve the efficiency of course orientation among medical students: a cross-sectional study — Gergely H. Fodor, Ferenc Rárosi, et al. · BMC Medical Education (2025) | TGRS Research Map | TGRS