The use of artificial intelligence and game‐based learning in removable partial denture design: A comparative study

Author:

Mahrous Ahmed12ORCID,Botsko David L.3,Elgreatly Amira4ORCID,Tsujimoto Akimasa567,Qian Fang8,Schneider Galen B.2

Affiliation:

1. Division of Prosthodontics Arizona School of Dentistry and Oral Health AT Still University Mesa Arizona USA

2. Department of Prosthodontics University of Iowa College of Dentistry Iowa City Iowa USA

3. Davenport Iowa USA

4. Division of Operative Dentistry Arizona School of Dentistry and Oral Health, AT Still University Mesa Arizona USA

5. Department of Operative Dentistry Aichi Gakuin University School of Dentistry Aichi, Nagoya Japan

6. Department of Operative Dentistry University of Iowa College of Dentistry Iowa City Iowa USA

7. Department of General Dentistry Creighton University School of Dentistry Omaha Nebraska USA

8. Division of Biostatistics and Computational Biology Iowa Institute for Oral Health Research University of Iowa College of Dentistry and Dental Clinics University of Iowa Iowa City Iowa USA

Abstract

AbstractPurposeThe 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.MethodsThe 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.ResultsPhase 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.ConclusionsThe 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.

Publisher

Wiley

Subject

General Medicine

Reference58 articles.

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