探讨ChatGPT在牙医学生技能教学中的应用能力:随机对照试验。

IF 5.8 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Siyu Huang, Chang Wen, Xueying Bai, Sihong Li, Shuining Wang, Xiaoxuan Wang, Dong Yang
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引用次数: 0

摘要

背景:临床手术技能训练是牙科学生临床前教育的重要组成部分。尽管虚拟现实和模拟器等技术辅助教学越来越多地被整合,但教师的直接指导仍然是技能发展的基石。ChatGPT是OpenAI开发的一种高级会话人工智能模型,正在逐步应用于医学教育。目的:本研究旨在比较ChatGPT辅助技能学习对临床手术技能教育的表现、认知负荷、自我效能感、学习动机和空间能力的影响,以评估ChatGPT在临床手术技能教育中的潜力。方法:本研究从国内某一流大学招收牙科本科学生187人,随机分为ChatGPT组和空白对照组。其中,对照组使用视频进行技能习得,ChatGPT组在视频的基础上使用ChatGPT。干预1周后,使用桌面虚拟现实测试技能,并通过眼动仪记录瞳孔直径的变化来测量认知负荷。此外,通过空间能力测试来分析ChatGPT对不同空间能力的人的影响。最后,采用调查问卷对学习过程中的认知负荷和自我效能感进行评估。结果:截至2024年10月25日,初步招募国内某一流大学牙科专业本科生192人。通过眼动追踪校准程序,5名参与者被排除在外,最终187名符合条件的学生在2024年11月2日前成功完成实验方案。通过随机分配进行短期干预后,表现优异(ChatGPT组:均值73.12,标准差10.06;对照组:平均65.54,标准差12.48;结论:ChatGPT在辅助牙科技能学习方面表现突出,本研究为ChatGPT融入技能教学提供了支持,为技能教学现代化提供了新思路。试验注册:ClinicalTrials.gov NCT06942130;https://clinicaltrials.gov/study/NCT06942130。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring the Application Capability of ChatGPT as an Instructor in Skills Education for Dental Medical Students: Randomized Controlled Trial.

Background: Clinical operative skills training is a critical component of preclinical education for dental students. Although technology-assisted instruction, such as virtual reality and simulators, is increasingly being integrated, direct guidance from instructors remains the cornerstone of skill development. ChatGPT, an advanced conversational artificial intelligence model developed by OpenAI, is gradually being used in medical education.

Objective: This study aimed to compare the effects of ChatGPT-assisted skill learning on performance, cognitive load, self-efficacy, learning motivation, and spatial ability, with the aim of evaluating the potential of ChatGPT in clinical operative skills education.

Methods: In this study, 187 undergraduate dental students recruited from a first-class university in China were randomly divided into a ChatGPT group and a blank control group. Among them, the control group used videos for skill acquisition, and the ChatGPT group used ChatGPT in addition to the videos. After 1 week of intervention, skills were tested using desktop virtual reality, and cognitive load was measured by recording changes in pupil diameter with an eye tracker. In addition, a spatial ability test was administered to analyze the effect of ChatGPT on those with different spatial abilities. Finally, a questionnaire was also used to assess cognitive load and self-efficacy during the learning process.

Results: A total of 192 dental undergraduates from a top-tier Chinese university were initially recruited for the experiment by October 25, 2024. Following eye-tracking calibration procedures, 5 participants were excluded, resulting in 187 eligible students successfully completing the experimental protocol by November 2, 2024. Following a short-term intervention administered through randomized allocation, superior performance (ChatGPT group: mean 73.12, SD 10.06; control group: mean 65.54, SD 12.48; P<.001) was observed among participants in the ChatGPT group, along with higher levels of self-efficacy (P=.04) and learning motivation (P=.02). In addition, cognitive load was lower in the ChatGPT group according to eye-tracking measures (ChatGPT group: mean 0.137, SD 0.036; control group: mean 0.312, SD 0.032; P<.001). The analysis of the learning performance of participants with different spatial abilities in the 2 modalities showed that compared to the learners with high spatial abilities (ChatGPT group: mean 76.58, SD 9.23; control group: mean 73.89, SD 11.75; P=.22), those with low spatial abilities (ChatGPT group: mean 70.20, SD 10.71; control group: mean 55.41, SD 13.31; P<.001) were more positively influenced by ChatGPT.

Conclusions: ChatGPT has performed outstandingly in assisting dental skill learning, and the study supports the integration of ChatGPT into skills teaching and provides new ideas for modernizing skill teaching.

Trial registration: ClinicalTrials.gov NCT06942130;https://clinicaltrials.gov/study/NCT06942130.

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来源期刊
CiteScore
14.40
自引率
5.40%
发文量
654
审稿时长
1 months
期刊介绍: The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.
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