聊天GPT-4o在为毕业的放射科医生制定持续专业发展计划的有效性:一项描述性研究
Minh Chau1, Elio Stefan Arruzza2, Kelly Spuur1
1Faculty of Science and Health, Charles Sturt University, Bathurst, NSW, Australia
Journal of educational evaluation for health professions
|November 18, 2024
概括
聊天GPT-4o可以帮助X光学学生进行持续专业发展 (CPD) 规划,与监管标准保持一致. 然而,人类监督对于确保个性化和特定环境的CPD计划至关重要.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 放射学 专业发展 放射学专业发展
背景情况:
- 持续的专业发展 (CPD) 对放射学从业者来说至关重要.
- 将CPD计划与澳大利亚医学辐射实践委员会 (MRPBA) 的监管要求保持一致,这是一项挑战.
- 像ChatGPT-4o这样的AI工具为结构化的CPD规划提供了潜在的解决方案.
研究的目的:
- 评估ChatGPT-4o在为X光学学生生成量身定制的CPD计划中的有效性.
- 评估人工智能生成的CPD计划是否符合MRPBA等监管机构的严格要求.
- 探索AI在支持放射学学生的专业发展方面的潜力.
主要方法:
- 使用了一种描述性,实验性的设计.
- 聊天GPT-4o为假设的毕业生X光学家生成了三个独特的CPD计划.
- 在MRPBA注册的学者评估基于适当性,及时性,相关性,反思性和完整性的计划.
主要成果:
- ChatGPT-4o生成的CPD计划通常符合监管标准.
- 统计分析显示,在场景 (弗里德曼测试) 中,评级者得分之间没有显著差异.
- 较低的类内相关系数 (ICC) 表明评级者之间存在显著的变化,特别是在及时性和完整性方面,突出了AI在个性化方面的局限性.
结论:
- 聊天GPT-4o在减少CPD规划和提供结构化支持的认知负载方面表现有希望.
- 人类监督是必不可少的,以确保CPD计划具有上下文相关性和反射性.
- 需要进一步的研究来增强人工智能个性化,以便在职业教育中有效评估CPD.
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