Applications of Artificial Intelligence-Driven Chatbots in University Level Dental Education: A Systematic Review.
5 affiliations
- 1Department of Oral Medicine and Radiology Dayananda Sagar College of Dental Sciences Kumaraswamy Layout Bangalore 560111 India dayanandasagar.edu.
- 2Department of Basic Medical and Dental Sciences College of Dentistry, Centre of Medical and Bio-Allied Health Science Research Ajman University Al Jurf, P.O. Box 346 Ajman UAE ajman.ac.ae.
- 3Department of Oral Pathology Dayananda Sagar College of Dental Sciences Kumaraswamy Layout Bangalore 560111 India dayanandasagar.edu.
- 4Department of Clinical Science College of Dentistry, Centre of Medical and Bio-Allied Health Science Research Al Jurf, P.O. Box 346 Ajman UAE.
- 5Oral Medicine and Radiology Department of Dental Surgery CAPFIMS AIIMS New Delhi India aiims.edu.
Abstract
Background
Artificial intelligence (AI), mainly AI-driven chatbots and large language models (LLMs) is reshaping dental education through adaptive, interactive, and simulation-based learning. While the transition in technology has been rapid, the evidence about the educational effectiveness of these technologies is still very diverse and not entirely directed.Aim
To analyze the roles, educational effectiveness, and impact of integrating AI-driven chatbots and LLMs in dental education at the university level with a focus on learning outcomes and implementation practices.Methods
The researchers conducted a thorough search of the electronic databases PubMed/MEDLINE, Scopus, Web of Science, and Embase for articles published from January 2018 to November 2025. This review met the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 criteria and was made up of original research articles on dental studentsand educators who were using AI-based chatbots as interventions. The outcomes measured were knowledge gain, clinical reasoning, diagnostic accuracy, communication skills, and engagement of learners. Due to the differences in the methodologies used the authors opted for a narrative synthesis approach.Results
Six studies met the eligibility criteria and showed potential benefits of AI-driven chatbots and LLMs for diagnostic reasoning, learning performance, engagement, and individualized feedback although methodological and outcome heterogeneity limited direct comparison.Conclusion
AI-driven chatbots and LLMs may complement university-level dental education, but their effectiveness and safe implementation require further rigorous evaluation.
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BibTeX
@article{b2026applications,
title = {{Applications of Artificial Intelligence-Driven Chatbots in University Level Dental Education: A Systematic Review.}},
author = {Ramnarayan B K and Raghad Hashim and Krishnanand P S and Vidya M A and Alexander Maniangat Luke and Usha C},
journal = {International journal of dentistry},
year = {2026},
month = nov,
doi = {10.1155/ijod/6612348},
url = {https://europepmc.org/article/MED/42968879},
note = {CC BY},
}
RIS
TY - JOUR
TI - Applications of Artificial Intelligence-Driven Chatbots in University Level Dental Education: A Systematic Review.
AU - Ramnarayan B K
AU - Raghad Hashim
AU - Krishnanand P S
AU - Vidya M A
AU - Alexander Maniangat Luke
AU - Usha C
PY - 2026
DA - 2026/11/01
JO - International journal of dentistry
DO - 10.1155/ijod/6612348
UR - https://europepmc.org/article/MED/42968879
AB - Background Artificial intelligence (AI), mainly AI-driven chatbots and large language models (LLMs) is reshaping dental education through adaptive, interactive, and simulation-based learning. While the transition in technology has been rapid, the evidence about the educational effectiveness of these technologies is still very diverse and not entirely directed.Aim To analyze the roles, educational effectiveness, and impact of integrating AI-driven chatbots and LLMs in dental education at the university level with a focus on learning outcomes and implementation practices.Methods The researchers conducted a thorough search of the electronic databases PubMed/MEDLINE, Scopus, Web of Science, and Embase for articles published from January 2018 to November 2025. This review met the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 criteria and was made up of original research articles on dental studentsand educators who were using AI-based chatbots as interventions. The outcomes measured were knowledge gain, clinical reasoning, diagnostic accuracy, communication skills, and engagement of learners. Due to the differences in the methodologies used the authors opted for a narrative synthesis approach.Results Six studies met the eligibility criteria and showed potential benefits of AI-driven chatbots and LLMs for diagnostic reasoning, learning performance, engagement, and individualized feedback although methodological and outcome heterogeneity limited direct comparison.Conclusion AI-driven chatbots and LLMs may complement university-level dental education, but their effectiveness and safe implementation require further rigorous evaluation.
SN - 1687-8728
SN - 1687-8736
ER -