Related Experiment Videos
Integrating Digital Feedback Into Competency-Based Medical Education for Crown Preparation Skill Acquisition: A
Tsung-Fu Chang1,2, Da-Yo Yuh1,2, Dun-Yu Hsu1,2
1Department of Family Dentistry and Oral Diagnosis, Tri-Service General Hospital, Taipei, Taiwan.
Introduction:
Digital technologies are increasingly incorporated into dental education to improve training and promote more objective skill assessment. Digital superimposition enables quantitative comparison between student preparations and reference models but is seldom applied in crown preparation training. Conventional methods using extracted teeth lack standardization and provide limited quantitative feedback. This study evaluated whether a digital superimposition-based assessment framework using standardized 3D-printed teeth yields objective measurements for expert-defined pass-fail evaluations of crown preparations.
Materials And Methods:
Thirty-three dental interns prepared crowns on standardized 3D-printed mandibular molar models. The preparations were scanned and digitally superimposed onto a predefined standard to calculate volumetric and surface area deviations. A single-group pre-post design was adopted to ensure educational equity in irreversible skill training. Pass-fail outcomes were determined through combined clinical and technical evaluations. Changes between pre-training (T1) and post-training (T2) assessments were analysed using McNemar's exact test and geometric discrepancies were examined for construct-related validity. After T2, the participants were surveyed for their perceptions.
Results:
The proportion of acceptable preparations increased significantly from 30.3% at T1 to 69.7% at T2, with no performance regression. Acceptable preparations showed significantly smaller volumetric and surface area deviations from the digital standard compared to non-acceptable preparations. The participants perceived high value in self-evaluation and interprofessional communication.
Conclusion:
Digital superimposition analysis using standardized 3D-printed models provides objective metrics of expert-defined preparation quality. This framework facilitates formative assessment within a competency-based medical education context and enhances interprofessional education by bridging the gap between clinical and technical standards.
