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Evaluation on a teaching software for removable partial denture framework design. | LitMetric

Evaluation on a teaching software for removable partial denture framework design.

Technol Health Care

Department of Prosthodontics, School and Hospital of Stomatology, Kunming Medical University, Kunming, Yunnan, China.

Published: October 2023

AI Article Synopsis

  • Removable partial dentures (RPDs) are commonly used dental prosthetics, and the study aimed to assess how design software influences preclinical teaching of RPDs.
  • Using Unreal Engine, researchers created teaching software and divided 131 stomatology students into three groups: traditional, flipped classroom, and software-based learning for evaluating RPD design skills.
  • Results showed that while overall theoretical knowledge scores were similar across groups, the software group performed significantly better in design tasks and reported higher levels of engagement, with most students finding the software effective for visualizing and understanding RPD concepts.

Article Abstract

Background: Removable partial dentures (RPDs) are widely used as a dental prosthesis and have a wide application scope.

Objective: To explore the effect of using design software in the preclinical teaching of removable partial dentures (RPDs).

Methods: Unreal Engine software was used to build the RPD framework design teaching and training software. All 131 undergraduate students majoring in stomatology in the class of 2018, Kunming Medical University, were randomly divided into three groups and received either traditional experiment teaching, flipped classroom teaching, or software teaching for RPD design. The application effect of the software in the preclinical teaching of RPD design was evaluated by analyzing the examination results and through the use of a questionnaire survey.

Results: The differences in the theoretical examination scores among the traditional teaching group, the flipped classroom group, and the software teaching group were not statistically significant (P> 0.05), while the average design scores of upper Kennedy Class I and lower Kennedy Class II subclass II in the software teaching group were significantly higher than those in the traditional teaching group (P< 0.05). Overall, 75% of the students in the software teaching group reported that this teaching method could improve their learning initiative, a higher percentage than in the traditional teaching group (55.8%, P< 0.05). Meanwhile, 90.9% of the students in the software teaching group reported that the software could make RPD-related theoretical knowledge more visual and intuitive, and 93.2% of these students felt it was helpful for understanding the RPD three-dimensional (3D) spatial structure. These percentages were higher than those in the traditional teaching and flipped classroom groups (P< 0.05).

Conclusion: In the preclinical teaching of RPD design, software training helped the students better understand the 3D structure of RPDs and establish clear design ideas, and it may also be valuable for in-depth research and promotion purposes.

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Source
http://dx.doi.org/10.3233/THC-220654DOI Listing

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