Large language model use in dental education: a cross-sectional multi-country study
Background Large language models (LLMs) are increasingly used in higher education, but multi-country evidence on dental students' use, verification, and integrity practices is limited. Objective To compare senior dental students' LLM use, perceived time and academic impact, reliability judgements, verification practices, and integrity safeguards across five countries. Methods An anonymous cross-sectional online survey was administered to final-year dental students in the United Arab Emirates (UAE), Jordan, Malay…
Final-year dental students reported frequent LLM use to save time and support learning, including clarifying and understanding complex concepts.
A quarter of students reported exam-time assistance, while consistent verification was low and awareness of institutional guidelines was limited.
Evidence
- Peer-reviewedMedical Education Online2026-08-06
How should this claim be treated?
Truvace Impact Record TRV-2026-0675, v1: “Large language model use in dental education: a cross-sectional multi-country study.” Truvace, 2026-08-07. /record/TRV-2026-0675 (accessed at citation time). sha256 474583fbbef7092b…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-0675 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.
ace