Augmented Reality Improved Knowledge and Efficiency of Root Canal Anatomy Learning: A Comparative Study

Author:

Alsalleeh Fahd1ORCID,Okazaki Katsushi2ORCID,Alkahtany Sarah1ORCID,Alrwais Fatemah1,Bendahmash Mohammad1,Al Sadhan Ra’ed3ORCID

Affiliation:

1. Restorative Dental Sciences, College of Dentistry, King Saud University, Riyadh 12372, Saudi Arabia

2. Department of Endodontics, New York University College of Dentistry, New York, NY 10010, USA

3. Oral Medicine & Diagnostic Sciences, College of Dentistry, King Saud University, Riyadh 12372, Saudi Arabia

Abstract

Teaching root canal anatomy has traditionally been reliant on static methods, but recent studies have explored the potential of advanced technologies like augmented reality (AR) to enhance learning and address the limitations of traditional training methods, such as the requirement for spatial imagination and the inability to simulate clinical scenarios fully. This study evaluated the potential of AR as a tool for teaching root canal anatomy in preclinical training in endodontics for predoctoral dental students. Six cone beam computed tomography (CBCT) images of teeth were selected. Board-certified endodontist and radiologist recorded the tooth type and classification of root canals. Then, STereoLithography (STL) files of the same images were imported into a virtual reality (VR) application and viewed through a VR head-mounted display. Forty-three third-year dental students were asked questions about root canal anatomy based on the CBCT images, and then, after the AR model. The time to respond to each question and feedback was recorded. Student responses were paired, and the difference between CBCT and AR scores was examined using a paired-sample t-test and set to p = 0.05. Students demonstrated a significant improvement in their ability to answer questions about root canal anatomy after utilizing the AR model (p < 0.05). Female participants demonstrated significantly higher AR scores compared to male participants. However, gender did not significantly influence overall test scores. Furthermore, students required significantly less time to answer questions after using the AR model (M = 4.09, SD = 3.55) compared to the CBCT method (M = 15.21, SD = 8.01) (p < 0.05). This indicates that AR may improve learning efficiency alongside comprehension. In a positive feedback survey, 93% of students reported that the AR simulation led to a better understanding of root canal anatomy than traditional CBCT interpretation. While this study highlights the potential of AR in learning root canal anatomy, further research is needed to explore its long-term impact and efficacy in clinical settings.

Funder

Abdul Latif Jameel General Trading Co. Ltd.

Publisher

MDPI AG

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3