揭示医学教师对人工智能融入医学教育的态度。

Khadija Farrukh Warraich
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引用次数: 0

摘要

目的:探讨教师对人工智能(AI)整合的态度,加快人工智能工具在医学教育中的适当适应。研究设计:定性案例研究。研究地点和时间:巴基斯坦卡拉奇巴利亚大学健康科学校区医学教育系,2023年6月至10月。研究方法:采用社会认知理论框架,采用定性案例研究设计。参与者是通过有目的的抽样技术来选择的。入选标准是具有5年教学经验且同意的教员。本研究采用有目的抽样方法,选取了21名参与者。数据收集使用个人投影访谈和两个焦点小组讨论使用光声方法。与会者听取了人工智能工具的介绍,这些工具可以整合到教学和评估中。采用模式匹配技术进行数据分析。结果:大多数参与者对人工智能工具的认识有限,这些工具可以整合到医学教育中,以增强教学和评估策略。然而,很少有参与者对人工智能及其用途有很好的理解。然而,教职员工的态度却大相径庭。与会者表示,应促进医疗机构、教育机构和科技公司之间的伙伴关系,以汇集资源和专业知识。教师们建议,应该有更多关于人工智能在医学教育中的应用的教师发展方案。结论:医学教师对人工智能融入医学教育的认识和意识有限,需要对其进行培训。关键词:人工智能,医学教育,医学院
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unveiling the Attitudes of Medical Faculty Towards the Integration of Artificial Intelligence in Medical Education.

Objective: To explore the attitude of faculty members towards integration of artificial intelligence (AI) and to accelerate the appropriate adaptation of AI tools in medical education.

Study design: A qualitative case study. Place and Duration of the Study: Department of Medical Education, Bahria University Health Sciences Campus, Karachi, Pakistan, from June to October 2023.

Methodology: A qualitative case study design was employed using a social cognitive theory framework. Participants were selected using a purposive sampling technique. Inclusion criteria were faculty members with five years of teaching experience and who gave consent. Twenty-one participants were included in the study using purposive sampling technique. Data were collected using individual projective interviews and two focus group discussions using the photovoice methodology. Participants were given a presention on tools of AI which can be integrated in teaching and assessment. Pattern matching technique was used for data analysis.

Results: Most of the participants had limited awareness of tools of AI that can be integrated in medical education to enhance teaching and assessment strategies. However, few participants had a good understanding of AI and its utility. However, there was great variation in the attitude of faculty members. Participants voiced on fostering partnerships between healthcare organisations, educational institutes, and technology companies to pool resources and expertise. Faculty members suggested that there should be more faculty development programmes on AI applications in medical education.

Conclusion: Medical faculty needs to be trained as they have limited knowledge and awareness of the integration of AI in medical education.

Key words: Artificial intelligence, Medical education, Medical faculty.

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