2022 European journal of dental ed…

3-Dimensional simulations and student learning in orthodontic education.

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European journal of dental education : official journal of the Association for Dental Education in Europe Vol. 26 (3) : 435-445 • Aug 2022

INTRODUCTION: The electronic dental model (e-model) is an example of a digital 3-dimensional technology to support inquiry-based learning in undergraduate dental education. As student perceptions of and engagement with e-models vary, it is uncertain whether these perceptions have implications for their learning processes and outcomes. MATERIALS AND METHODS: Third-year dental students (N = 40) completed a questionnaire to identify their perceptions of and preferences for model modalities. They were divided into three groups based on their preference: Preferring plaster models (Group 1); Preferring e-models (Group 2); No preference (Group 3). Students from three groups (N = 9) attended a hands-on digital occlusion evaluation workshop, and then completed a case-based diagnostic evaluation test using digital occlusion evaluation software. Camtasia Studio recorded real-time and on-screen data of the number of mouse-clicks and time spent. RESULTS: Students reported positive feedbacks on the use of e-models, and 72.5% of the students preferred combination use of e-models and plaster models. After attending the hands-on digital dental occlusion evaluation workshop, Group 2 scored higher on the diagnostic evaluation test (p < .05) and registered more mouse-clicks than Group 1 when evaluating the arch symmetry (p < .05). Group 2 registered fewer mouse-clicks than Group 3 during tooth size measurement (p < .05). There was no significant difference regarding the time used to answer the knowledge questions amongst the three groups. CONCLUSION: Undergraduate dental students indicated a generally high acceptance of e-models for their learning in orthodontics, and more prefer a blended approach. Students preferring e-models presented higher performance outcomes, which supports cognitive load theory regarding prior exposure to simulation-based environments.

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