Objectives: Incorporating artificial intelligence (AI) in assessing dental students' knowledge and skills is in its infancy, despite AI being well established as an aid to aspects of clinical diagnosis and education. This study aimed to investigate whether dental educators perceived AI as beneficial in assessing students.
Methods: This was a mixed methods study where quantitative and qualitative data were generated through a live online polling system, Vevox . Quantitative data were collected, findings of which were immediately shared with dental educators attending the workshop at a European wide dental educators' conference. Qualitative data were collected at the workshop via word clouds as part of the online questions, and by asking participants to write down their views, opinions and reflections. Analysis was descriptive and thematic respectively.
Results: 51 conference delegates attended the workshop. 14 questions had a response rate of over 69%, two questions had response rates of 53% and 57% respectively. 65% (n=33) of participants considered that their dental school provided support and training in using AI. Dental educators were uncertain whether assessments of dental students generated by AI were effective in testing students' knowledge/competence, 47% (n=18). One third of the participants were sure that AI generated assessments were more effective (34%; n=13). Less than half the participants were confident in using AI in assessing dental students (2.24/4; [SD 1.0588]). Thematic analysis revealed key themes: training, effectiveness of AI assessment, current use of AI, concerns, confidence, and advantages/disadvantages.
Conclusions: This study illustrated the diversity in knowledge, confidence and application of AI in the assessment of dental students, and the need for universities and dental schools to invest time and expertise in supporting dental educators in this important area.
Clinical Significance: The education and assessment of dental students should ensure that caring, knowledgeable and skilful practitioners are entrusted with patients care. The use of Artificial Intelligence to support or replace previous assessment techniques need to be understood by dental educators, to ensure that the assessments are robust, validated and workable.
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http://dx.doi.org/10.1016/j.jdent.2025.105676 | DOI Listing |
Int Dent J
March 2025
Department of Restorative Dentistry, College of Dentistry, Ajman University, Ajman, United Arab Emirates; Centre of Medical and Bio-allied Health Sciences Research, Ajman University, Ajman, United Arab Emirates.
Artificial intelligence (AI) holds immense promise in revolutionising dentistry, spanning, diagnostics, treatment planning and educational realms. This narrative review, in two parts, explores the fundamentals and the multifaceted potential of AI in dentistry. The current article explores the profound impact of AI in dentistry, encompassing diagnostic tools, treatment planning, and patient care.
View Article and Find Full Text PDFEur J Dent
March 2025
Department of Clinical Sciences, College of Dentistry, Ajman University, Ajman, United Arab Emirates.
Interprofessional education (IPE) and interprofessional collaborative practice have gained significant recognition for their ability to enhance health care education and improve patient outcomes, particularly in dentistry. Given the close connection between oral and general health, incorporating IPE into dental curricula has become essential in preparing practitioners for collaborative patient-centered care. This review focuses on the foundations of IPE in dental schools, focusing on its role in preparing students for collaborative health care.
View Article and Find Full Text PDFEur J Dent
March 2025
Department of Dental Materials Science, Academic Centre for Dentistry Amsterdam (ACTA), Universiteit van Amsterdam and Vrije Universiteit, Amsterdam, North Holland, the Netherlands.
Objectives: This article evaluates the marginal and internal gap, interfacial volume, and fatigue behavior in computer-aided design-computer-aided manufacturing (CAD-CAM) restorations with different designs (crowns or endocrowns) made from lithium disilicate-based ceramic (LD, IPS e.max CAD, Ivoclar AG) or resin composite (RC, Tetric CAD, Ivoclar AG).
Materials And Methods: Simplified LD and RC crowns (-C) and endocrowns (-E) were produced ( = 10) using CAD-CAM technology, through scanning (CEREC Primescan, Dentsply Sirona) and milling (CEREC MC XL, Dentsply Sirona), and then adhesively bonded to fiberglass-reinforced epoxy resin.
Eur J Dent
March 2025
Department of Community Dentistry, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand.
Objectives: This study aims to explore the beliefs and attitudes related to the adoption of teledentistry among Pakistani dental professionals, focusing on data security, practice enhancement, and patient benefits.
Material And Methods: A cross-sectional study on a 5-point Likert scale assessed four domains of teledentistry: data security and patient consent, practice improvement capabilities, usefulness for dental practice, and patient benefits, among dental professionals through electronic forms. Demographic data and items from four domains were analyzed by descriptive statistics, analysis of variance and Pearson's correlation tests, respectively, using SPSS, with a -value of < 0.
J Dent
March 2025
UCL Eastman Dental Institute, Rockefeller Building, 21 University Street, London, WC1E 6DE, UK.
Objectives: Incorporating artificial intelligence (AI) in assessing dental students' knowledge and skills is in its infancy, despite AI being well established as an aid to aspects of clinical diagnosis and education. This study aimed to investigate whether dental educators perceived AI as beneficial in assessing students.
Methods: This was a mixed methods study where quantitative and qualitative data were generated through a live online polling system, Vevox .
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