This study aims to compare traditional faculty-based assessment with two AI-assisted digital self-assessment software programs for evaluating tooth preparations for metal-ceramic crowns for undergraduate dental preclinical students at College of Dentistry El Alamein, AAST in terms of: (1) Accuracy of preparation outcomes, (2) Student learning outcomes over a training period.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
SINGLE
Enrollment
36
Students in NMG used a license-free 3D comparison workflow (Medit Link/Compare, Compare tool; Medit Compare v3.4.9; Medit) to superimpose the prepared-tooth scan (TT-STL) onto the unprepared reference scan (RTS-STL).
Students in MG used metrology-grade 3D inspection software (Geomagic Control X v2018.1.1; 3D Systems)to superimpose TT-STL onto RTS-STL. Initial Alignment was performed followed by Best Fit Alignment (iterative closest point registration).
Students in TG assessed reduction with a silicone putty index and a periodontal probe across the previously predefined regions. Feedback was provided by experienced instructors (≥5 years of clinical teaching experience) using the same regional assessment approach.
College of Dentistry El Alamein - AAST
El Alamein, Egypt
RECRUITINGChange in preparation scores
Preparations were scored with a prespecified 10-item rubric derived from ADEX criteria for mandibular first molar metal-ceramic crown preparation (overall score 0-10). Each item was rated on a 3-level scale (0, 0.5, or 1) and summed to obtain a total score
Time frame: Up to 5 weeks
RMS deviation from the ideal preparation
all the resulting TT-STL files across all sessions (from 1-5) of the study of the three groups of prepared teeth were compared with the ideal preparation
Time frame: Up to 5 weeks
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