Amira Elgreatly

Purpose: The purpose of this study was to compare student performance in removable partial denture (RPD) design during a pre‐clinical RPD course with and without using a recently developed computer software named AiDental. Additionally, student perceptions associated with the use of this software were assessed.Methods: The AiDental software consists of a learning environment containing an RPD design system that automatically designs RPDs based on the user's input. The software also contains an RPD game component that compares the user's RPD Design to an automatically generated RPD ideal design. The study was conducted in two phases. In phase one, pre‐clinical second‐year dental students who participated in the study were randomly divided into two groups: The AiDental group with AiDental software access (n = 36), and the conventional group without software access (n = 37). Both groups received conventional RPD instruction and practice, however, the AiDental group had additional access to the AiDental software. After 2 weeks, both groups took a mock practical test, which was collected and graded by the principal investigator (PI). The PI was blinded from group assignment and no identifying information was used in the mock practical. In phase two, all students were granted access to the AiDental software for the remainder of the pre‐clinical course duration. At the conclusion of the course, all students were given a survey to evaluate their perceptions of the AiDental software. Descriptive statistics were calculated and analyzed. Variables related to perceptions of both the AiDental designer and game were assessed using Spearman's rank correlation test, the chi‐square test, Fisher's exact test, and the non‐parametric Wilcoxon rank‐sum test as appropriate. In addition, a thematic analysis of the responses to the optional comments section was conducted using the Braun and Clarke method.Results: Phase one results showed that subjects in the AiDental group were more likely than subjects in the conventional group to receive a final grade of A or B. Phase two results showed generally favorable student perceptions towards the software, and additionally, the results showed that age was significantly negatively correlated with ease of use of the software, improving decision‐making, and critical thinking relative to RPD design choices. However, no correlation between age and using the software as a reference were noted.Conclusions: The use of AiDental's automated feedback and gamification techniques in RPD education had a positive effect on student grades and it was well‐liked by students. Thus, the results suggest that AiDental has the potential to be a useful adjunct to pre‐clinical teaching.

Purpose/Objectives: To assess student perceptions on learning dental anatomy using natural extracted teeth, 3D printed models, 3D virtual models, and augmented reality (AR) technology. Methods: Eighty first‐year dental students enrolled in the dental anatomy course were instructed to examine four stations. The stations included four versions of a mandibular first molar: an extracted natural tooth, a 3D printed model, a 3D virtual model, and a model displayed on a novel AR device. After examining all stations, the students were asked to complete an electronic survey. Bivariate analysis was performed to determine whether students’ perceptions are related to their demographic characteristics and technological experience with computer use, 3D modeling, and video games. Results: Seventy students completed the survey (87.5% response rate). Students rated natural teeth to have the highest educational value, the 3D printed tooth to be the most accessible, and the AR application to be the most interesting modality. Students who played little to no video games were more likely to rate AR as high educational value (48.8% vs. 10.3%; p < 0.001), while students with little 3D modeling experience were more likely to rate high accessibility of the 3D Model (78.1% vs. 48.3%; p < 0.001). No statistically significant associations between the perceptions and students’ demographic characteristics or use of computer were noted.Conclusion: The natural extracted tooth was rated highest in educational value, while the 3D printed model was rated easiest to use, and the AR model was the most interesting to the students.

In order to provide restorations and dental prostheses that are esthetically pleasing, functional and in harmony with a patient's occlusion, practitioners must have a thorough knowledge of dental anatomy. Recent studies have shown that virtual three‐dimensional (3D) models greatly enhance educational outcomes in dental anatomy courses. This article describes a novel educational technique and uses videos and web‐based portals to demonstrate how to create a virtual 3D tooth model from a scan of a natural tooth for use in dental anatomy courses.