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        Rating criteria to evaluate student performance in digital wax-up training using multi-purpose software

        Takuya Mino,Yoko Kurosaki,Kana Tokumoto,Takaharu Higuchi,Shinichi Nakanoda,Ken Numoto,Ikue Tosa,Aya Kimura-Ono,Kenji Maekawa,Tae Hyung Kim,Takuo Kuboki 대한치과보철학회 2022 The Journal of Advanced Prosthodontics Vol.14 No.4

        PURPOSE. The aim of this study was to introduce rating criteria to evaluate student performance in a newly developed, digital wax-up preclinical program for computer-aided design (CAD) of full-coverage crowns and preliminarily investigate the reliability and internal consistency of the rating system. MATERIALS AND METHODS. This study, conducted in 2017, enrolled 47 fifth-year dental students of Okayama University Dental School. Digital wax-up training included a fundamental practice using computer graphics (CG), multipurpose CAD software programs, and an advanced practice to execute a digital waxup of the right mandibular second molar (#47). Each student’s digital wax-up work (stereolithography data) was evaluated by two instructors using seven qualitative criteria. The total qualitative score (0-90) of the criteria was calculated. The total volumetric discrepancy between each student’s digital wax-up work and a reference prepared by an instructor was automatically measured by the CAD software. The inter-rater reliability of each criterion was analyzed using a weighted kappa index. The relationship between the total volume discrepancy and the total qualitative score was analyzed using Spearman’s correlation. RESULTS. The weighted kappa values for the seven qualitative criteria ranged from 0.62 - 0.93. The total qualitative score and the total volumetric discrepancy were negatively correlated (ρ = -0.27, P = .09, respectively); however, this was not statistically significant. CONCLUSION. The established qualitative criteria to evaluate students’ work showed sufficiently high inter-rater reliability; however, the digitally measured volumetric discrepancy could not sufficiently predict the total qualitative score.

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