Journal
JOURNAL OF PROSTHETIC DENTISTRY
Volume 121, Issue 1, Pages 95-100Publisher
MOSBY-ELSEVIER
DOI: 10.1016/j.prosdent.2018.01.004
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Funding
- Institute for Information & Communications Technology Promotion - Korean government [B0101-17-1081]
- Industrial Strategic Technology Development Program - Ministry of Trade, Industry Energy (Korea) [10062635]
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Statement of problem. Dental clinical procedures are being replaced by digital workflows. Therefore, the time necessary to learn dental computer-aided design (CAD) software to achieve a change in the digital workflow should be evaluated. Purpose. The purpose of this study was to predict the learning curve according to the type of dental CAD software with the Wright model and to determine the rate of improvement in the learner's working time with iterative learning. Material and methods. A total of 40 participants with various degrees of experience with dental computer-aided design and computer-aided manufacturing (CAD-CAM) systems were recruited. The 4 specified steps of a custom abutment design were performed with 3DSystem CAD software (Daesung) and exocad DentalCAD (exocad GmbH) software and were repeated 3 times in stages. The times were analyzed with repeated-measures 1-factor and 2-factor analyses. The learning time for 300 design iterations was estimated by applying the Wright model formula, and the 300-repetition times were analyzed with the Mann-Whitney U test (alpha=.05). Results. exocad had a longer mean learning time than the 3DSystem. The overall change with repeated learning was significantly different (P<.001), and all differences were found in the first to third iterations. Software-dependent differences were also observed (P=.005). The Mann-Whitney U test also revealed a significant difference between the 2 software programs (P=.015), but no significant difference was found after the 56th iteration (57th iteration: P=.051). Conclusions. As the time reduction patterns for iterative learning differ depending on the type of CAD software, the learning curves may differ according to the type of software. As the operator's skill increased through iterative learning, the differences in learning times between the software programs gradually disappeared.
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