講演情報
[IO-9]Objective evaluation in dental digital sculpting education
*Juan Marcelo Rosales1, Kaori Eguchi1, Masaru Kaku1 (1. Division of Bio-prosthodontics, Faculty of Dentistry & Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan.)
[Objective]
CAD/CAM technology in dentistry has become an essential component in dental treatment, consequently, in dental education. Niigata University offers a training program covering dental sculpting using both conventional wax-up and digital approaches. However, students’ skill assessment remains challenging due to the lack of reliable objective evaluation methods. To assess the product accuracy, coefficient of variance (CV) has been calculated based on the mean and standard deviation (SD) of volumetric measurements, however, substantial variability of the products can bias the assessment. In this study, to assess the CV, we employ potentially more reliable parameters such as statistical mode (SM), indicating the distribution tendency, and interquartile range (IQR), representing the dispersion range of the differences in the products. The aim of this study was to evaluate the CV of students’ products using SM and IQR parameters instead of the conventional mean and SD.
[Method]
Three-dimensional tooth models (C12-AT1A 32S, Nissin) were digitized to serve as reference models. The detailed structure of the models was flattened and used as base models. Students digitally sculpted the base model using a web browser-based SculptGL software. For evaluation, reference and product models were superimposed and Housedorf distances were calculated. CV using mean and SD for CV(SD), and SM and IQR for CV(IQR) were calculated, and discrepancies were analyzed.
[Results and Discussion]
Results showed discrepancies in the score ranking table between the two methods. CV(SD) showed higher sensitivity to outliers, resulting in lower grade due to the wide dispersion of data points. In contrast, CV(IQR) demonstrated less variability. CV(IQR) evaluation can consider the balance between size and shape of the products, consequently, slight deviations in size seems to be tolerated if the overall shape is maintained. These results suggest that the combination of the SM and IQR parameters for calculation of CV may provide a more reliable assessment of student performance compared to the mean and SD.
CAD/CAM technology in dentistry has become an essential component in dental treatment, consequently, in dental education. Niigata University offers a training program covering dental sculpting using both conventional wax-up and digital approaches. However, students’ skill assessment remains challenging due to the lack of reliable objective evaluation methods. To assess the product accuracy, coefficient of variance (CV) has been calculated based on the mean and standard deviation (SD) of volumetric measurements, however, substantial variability of the products can bias the assessment. In this study, to assess the CV, we employ potentially more reliable parameters such as statistical mode (SM), indicating the distribution tendency, and interquartile range (IQR), representing the dispersion range of the differences in the products. The aim of this study was to evaluate the CV of students’ products using SM and IQR parameters instead of the conventional mean and SD.
[Method]
Three-dimensional tooth models (C12-AT1A 32S, Nissin) were digitized to serve as reference models. The detailed structure of the models was flattened and used as base models. Students digitally sculpted the base model using a web browser-based SculptGL software. For evaluation, reference and product models were superimposed and Housedorf distances were calculated. CV using mean and SD for CV(SD), and SM and IQR for CV(IQR) were calculated, and discrepancies were analyzed.
[Results and Discussion]
Results showed discrepancies in the score ranking table between the two methods. CV(SD) showed higher sensitivity to outliers, resulting in lower grade due to the wide dispersion of data points. In contrast, CV(IQR) demonstrated less variability. CV(IQR) evaluation can consider the balance between size and shape of the products, consequently, slight deviations in size seems to be tolerated if the overall shape is maintained. These results suggest that the combination of the SM and IQR parameters for calculation of CV may provide a more reliable assessment of student performance compared to the mean and SD.