在护理心理学教育中应用人工智能-人类智能协作认知学徒模式:一个解释性的顺序混合方法研究
Jiasi Li1, Yingying Wang1, Xinyu Zhu1
1School of Nursing, Guangzhou Medical University, Guangzhou, China.
Nurse education in practice
|January 31, 2026
概括
一个新的人工和人类智能 (AI-HI) 模型改善了护理学生的知识和临床技能. 这种AI-HI方法提供了一个有希望的数字解决方案,用于在护理教育中整合理论和实践.
科学领域:
- 护理教育 护理教育
- 教育技术的教育技术
- 医疗保健中的人工智能
背景情况:
- 护理理论和临床实践之间的差距是一个持续的挑战.
- 现有的数字平台往往提供碎片化的知识,缺乏个性化的支持.
- 这限制了护理学生的综合理解和基本临床技能的发展.
研究的目的:
- 评估一个整合人工智能和人类智能的结构化认知学徒模式 (AI-HI) 的有效性.
- 加强护理学生的心理护理教育,专注于知识掌握和实践技能.
- 探索AI-HI模型影响的潜在机制.
主要方法:
- 采用了一种解释性的顺序混合方法设计.
- 参与者 (n=66) 被随机分配到AI-HI协作平台组或标准在线课程 (SPOC) 组.
- 通过理论测试和客观结构化临床检查 (OSCE) 评估学习成果,随后进行定性焦点小组采访.
主要成果:
- 与对照组相比,AI-HI组在理论知识 (p=0.012) 和欧安组织 (OSCE) (p<0.001) 方面的得分明显更高.
- 定性发现强调了教师-人工智能合作在积极学习中的认知支架作用.
- 技术挑战被认为是影响学生参与度的一个因素.
结论:
- AI-HI协作结构认知学徒模式显示了护理教育的重大前景.
- 这种方法有效地提高了知识整合和临床推理能力.
- 它为利用数字工具提供了有价值的见解,以弥合护理中的理论与实践差距.
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