ArticleEuropean journal of dental education : official journal of the Association for Dental Education in Europe2026
Evaluating Dental Students' Perspectives on Artificial Intelligence (AI)-Driven Large Language Models in Education in Saudi Arabia.
Article in European journal of dental education : official journal of the Association for Dental Education in Europe, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- Large language model use in dental education: a cross-sectional multi-country study.Medical education online · 2026Article
- DentalEdu-AI graph: mapping evidence-grounded and knowledge-structured AI for dental education, assessment, and accuracy.The Saudi dental journal · 2026Article
- Evaluating Dental Students' Perspectives on Artificial Intelligence (AI)-Driven Large Language Models in Education in Saudi Arabia.European journal of dental education : official journal of the Association for Dental Education in Europe · 2026Article
- Factors influencing large language model adoption among dental students: a cross-sectional study.Scientific reports · 2026Article
- Dentists' awareness of data security and ethical issues during the transition to artificial intelligence-driven clinical practice.Acta odontologica Scandinavica · 2026Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThis study explores the perspectives of dental students in Saudi Arabia regarding the integration of large language models (LLMs) in dental education. It aims to understand their familiarity, utilisation and perceptions of these tools, while addressing the potential benefits, risks, and ethical considerations associated with their use.
methodsA cross-sectional survey was conducted between January and March 2024, involving 1370 dental students from various institutions across Saudi Arabia. The survey included multiple-choice questions and Likert scale items, assessing familiarity, usage patterns, and perceptions of LLMs. Statistical analyses were performed to identify significant associations between demographic variables and students' familiarity, utilisation, and perceptions of LLMs.
resultsThe survey revealed broad familiarity with LLMs, with 58.1% of participants being aware of their capabilities. Usage patterns varied, with high engagement in tools like ChatGPT and Google Translate. Significant gender, educational level and regional differences were observed, with males and postgraduate residents showing higher familiarity and utilisation rates. However, ethical concerns, including the potential for plagiarism and academic dishonesty, were prevalent, with only 15% of students reporting that their institutions had specific guidelines for LLM use.
conclusionThe study highlights the need for a controlled and ethically informed approach to integrating LLMs into dental education. While LLMs offer potential benefits, their use must be regulated to prevent misuse and ensure that educational outcomes are enhanced rather than compromised. Institutions should develop clear guidelines, provide ethical training and emphasise the importance of critical evaluation when using LLMs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.