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Artificial Intelligence in Dental Education: Overview of Teaching, Assessment and Academic Performance Prediction.

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Τίτλος: Artificial Intelligence in Dental Education: Overview of Teaching, Assessment and Academic Performance Prediction.
Συγγραφείς: Chuenjitwongsa S; Dental Education Unit, Office of Academic Affairs, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand., Arunratanothai T; Dental Education Unit, Office of Academic Affairs, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand., Rewthamrongsris P; Department of Anatomy, Center of Excellence for Dental Stem Cell Biology, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand; Center of Artificial Intelligence and Innovation, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand., Sumrejkanchanakij P; Dental Education Unit, Office of Academic Affairs, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand; Department of Anatomy, Center of Excellence for Dental Stem Cell Biology, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand., Tavedhikul K; Dental Education Unit, Office of Academic Affairs, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand; Department of Periodontology, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand., Samaranayake LP; Department of Periodontology, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand; Global Research Cell, Dr. D. Y. Patil Dental College and Hospital, Dr. D. Y. Patil Vidyapeeth, Pune, India; Faculty of Dentistry, The University of Hong Kong, SAR China., Osathanon T; Dental Education Unit, Office of Academic Affairs, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand; Department of Anatomy, Center of Excellence for Dental Stem Cell Biology, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand; Center of Artificial Intelligence and Innovation, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand. Electronic address: thanaphum.o@chula.ac.th.
Πηγή: International dental journal [Int Dent J] 2026 Oct; Vol. 76 (5), pp. 109733. Date of Electronic Publication: 2026 Jul 11.
Τύπος έκδοσης: Journal Article; Review
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Elsevier Country of Publication: England NLM ID: 0374714 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1875-595X (Electronic) Linking ISSN: 00206539 NLM ISO Abbreviation: Int Dent J Subsets: MEDLINE
Imprint Name(s): Publication: 2021- : London : Elsevier
Original Publication: London : FDI World Dental
Ιατρικοί όροι (MeSH): Education, Dental*/methods , Artificial Intelligence* , Academic Performance* , Educational Measurement*, Humans ; Teaching ; Generative Artificial Intelligence
Περίληψη: Artificial Intelligence (AI) is increasingly used in dental education. The present study aimed to examine the current landscape of AI applications in dental education, focusing on their impact on teaching, assessment, and the prediction of academic performance. A literature search was performed based on articles published between November 2014 and March 2026 in the PubMed and Scopus databases. Studies focusing on AI applications in dental education were analysed across the domains: teaching and learning, assessment, and academic performance prediction. Forty-two publications met the inclusion criteria and were used as the evidential basis for this study. AI integration emphasised fundamental knowledge, use cases, and evaluation in teaching and learning. AI tools such as chatbots, simulations, and generative models enhanced student engagement and learning efficiency while supporting clinical decision-making. AI-assisted tasks, including radiograph interpretation and scientific writing, demonstrated improved outcomes. For assessment, AI showed moderate to high correlations with human evaluators for essay grading and thematic analysis. Further, AI models could forecast student outcomes, supporting personalised learning strategies and early intervention. AI applications have a vast potential to enhance dental education, particularly in improving teaching efficiency, personalised learning, self-directed learning, and assessment accuracy. Curriculum revisions and faculty training are necessary to fully integrate AI responsibly, leveraging its capabilities while maintaining the critical role of human oversight in education.
(Copyright © 2026 The Authors. Published by Elsevier Inc. All rights reserved.)
Competing Interests: Conflict of Interest None disclosed.
Contributed Indexing: Keywords: Artificial Intelligence; Dental Education; Health Professions Education; Pedagogy
Entry Date(s): Date Created: 20260711 Date Completed: 20260916 Latest Revision: 20260916
Update Code: 20260916
PubMed Central ID: PMC13381989
DOI: 10.1016/j.identj.2026.109733
PMID: 42435734
Βάση Δεδομένων: MEDLINE
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  Data: Artificial Intelligence (AI) is increasingly used in dental education. The present study aimed to examine the current landscape of AI applications in dental education, focusing on their impact on teaching, assessment, and the prediction of academic performance. A literature search was performed based on articles published between November 2014 and March 2026 in the PubMed and Scopus databases. Studies focusing on AI applications in dental education were analysed across the domains: teaching and learning, assessment, and academic performance prediction. Forty-two publications met the inclusion criteria and were used as the evidential basis for this study. AI integration emphasised fundamental knowledge, use cases, and evaluation in teaching and learning. AI tools such as chatbots, simulations, and generative models enhanced student engagement and learning efficiency while supporting clinical decision-making. AI-assisted tasks, including radiograph interpretation and scientific writing, demonstrated improved outcomes. For assessment, AI showed moderate to high correlations with human evaluators for essay grading and thematic analysis. Further, AI models could forecast student outcomes, supporting personalised learning strategies and early intervention. AI applications have a vast potential to enhance dental education, particularly in improving teaching efficiency, personalised learning, self-directed learning, and assessment accuracy. Curriculum revisions and faculty training are necessary to fully integrate AI responsibly, leveraging its capabilities while maintaining the critical role of human oversight in education.<br /> (Copyright © 2026 The Authors. Published by Elsevier Inc. All rights reserved.)
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  Data: Conflict of Interest None disclosed.
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