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Related Experiment Video

Updated: May 24, 2026

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
05:49

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images

Published on: February 23, 2024

Integrating artificial intelligence into dental student assessments: Current & future status.

P D Fine1, C Louca2, I Tonni3

  • 1UCL Eastman Dental Institute, London, UK.

Journal of Dentistry
|May 22, 2026
PubMed
Summary

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Artificial Intelligence (AI) integration in dental education assessment is nascent, with limited adoption by educators due to knowledge gaps and apprehension. Further support and guidance are crucial for effective AI implementation in dental student evaluation.

Area of Science:

  • Medical Education
  • Dental Education Technology
  • Artificial Intelligence in Healthcare

Background:

  • Artificial Intelligence (AI) integration in medical and dental education is cautiously optimistic.
  • While AI in healthcare assessment is established, its use in dental student assessment is emerging.
  • Dental educators report limited AI use due to a lack of support, confidence, and knowledge.

Purpose of the Study:

  • To investigate international dental educators' perceptions and experiences with integrating AI into dental student assessment.
  • To identify facilitators and barriers to AI adoption in dental education.
  • To enhance student learning through AI-supported assessment strategies.

Main Methods:

  • A mixed-methods study utilizing a live online polling platform (Vevox™) during a European dental educators' conference.
Keywords:
Artificial intelligenceDental educatorsDental student assessmentEuropeanPerspective

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Last Updated: May 24, 2026

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
05:49

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images

Published on: February 23, 2024

  • Data collection involved a workshop setting focusing on AI's impact on traditional assessment, effectiveness, and student learning.
  • Quantitative data were analyzed descriptively, and qualitative data were analyzed thematically.

    • Main Results:

    • 152 dental educators participated; 29.13% currently use AI in student assessment.
    • Multiple Choice Questions (MCQs) were the most common AI-assisted assessment (31.25%).
    • Only one participant reported using AI for reflective portfolios, indicating limited application.

    Conclusions:

    • International dental educators are in the early stages of AI integration for student assessment.
    • Apprehension persists, highlighting the need for educator support and training.
    • Clear recommendations and guidance are necessary to overcome challenges and leverage AI for robust dental student evaluation.