Purpose: The first purpose of this in vitro study was to predict the learning curve of dental computer-aided design (CAD) software programs according to dental personnel and type of dental CAD software using the Wright model and to investigate the ten...
Purpose: The first purpose of this in vitro study was to predict the learning curve of dental computer-aided design (CAD) software programs according to dental personnel and type of dental CAD software using the Wright model and to investigate the tendency of dental personnel to reduce working time based on repeated learning. Another purpose of this study was to compare the correlation between the learning effect of the dental CAD software and computer literacy in the clinical and preclinical experience groups of CAD/computer-aided manufacturing.
Materials and methods: A total of 36 participants were recruited, including an equal number of dentists, dental technicians, and dental students (N = 12 per dental personnel). A custom abutment design was evaluated using exocad CAD and Deltanine CAD software programs. The design was carried in four steps, repeated three times each. This study applied the formula of the Wright model to predict the number of repetitions. A survey was conducted to evaluate the participants’ computer literacy. In the statistical analysis, 3-repetition and 500-repetition times were analyzed using the Kruskal–Wallis H test and Friedman test (α = 0.05), and a post-hoc comparison was performed using the Mann–Whitney U test and Bonferroni correction method (α = 0.017). The Mann–Whitney U test was used to analyze the difference between the clinical and preclinical experience groups, and the correlation between computer literacy and reduction in working time was confirmed by Spearman’s rank correlation analysis (α = 0.05).
Results: Participants had a longer mean learning time with the exocad CAD software than with the Deltanine CAD software. The overall change with repeated learning was significantly different (P < 0.001), and all differences were found in the first to third iteration trials. Software-dependent differences were also observed (P = 0.005). The Mann–Whitney U test also revealed a significant difference between the two software programs (P = 0.015), but no significant difference was detected after the 56th iteration trials (57th iteration trials: P = 0.051). Three repetitions resulted in a shorter working time in the dental technician group. The three-repetition time decreased statistically among all dental personnel (P < 0.001). There was a statistically significant difference in the time for 500 repetitions based on the type of dental personnel (P = 0.036), but no significant difference was found after the fourth iteration trials (fifth iteration trials: P = 0.076). Furthermore, there was a statistically significant decrease in the estimated time of 500 iteration trials from the first to the 500th iteration trials (P < 0.001). The median working time indicated that the clinical experience group was faster than the preclinical experience group (P < 0.001). On the other hand, the preclinical experience group had a greater reduction in working time (P = 0.002). Only the preclinical experience group had a significant positive correlation between the computer literacy and reduction in working time (P < 0.001).
Conclusions: Because the time-reduction patterns for iterative trials differ depending on the type of CAD software, the learning curves might also differ based on software type. As the operator’s skill increased through iterative trials, the differences in learning times between the software programs gradually disappeared. All dental personnel showed learning effects of dental CAD software programs. Although the dental technician group initially showed a short working time, after initial learning, the same learning effect appeared, regardless of the type of dental personnel. Basic computer skills are required for first-time users to achieve an excellent learning effect with dental CAD software programs.