人机协同教学模式下新入职护士规范化培训体系的构建
Construction of the Standardized Training System for Newly Recruited Nurses under the Human-Machine Collaborative Teaching Mode
摘要: 目的:构建人机协同教学模式下新入职护士规范化培训体系的构建,为新入职护士的规范化培训提供参考。方法:通过文献分析、课题组讨论初步拟定人机协同教学模式下新入职护士规范化培训体系,采用德尔菲法对17名护理管理、护理教育、临床护理专家进行2轮咨询。结果:2轮专家的积极系数均为100%,权威系数为0.90。最终形成的人机协同教学模式下新入职护士规范化培训体系内容包含6个一级指标、17个二级指标,64个三级指标。结论:人机协同教学模式下新入职护士规范化培训体系具有一定的科学性、创新性、实用性,可为医疗机构开展新入职护士规范化培训提供参考。
Abstract: Objective: To develop a standardized training system for newly recruited nurses under human-machine collaborative teaching mode, providing reference for standardized nurse training programs. Methods: Through literature analysis and group discussions within the research team, a preliminary framework for the standardized training system of newly recruited nurses under the human-machine collaborative teaching model was initially formulated. Two rounds of Delphi consultations were conducted with 17 experts in nursing management, nursing education, and clinical practice. Results: Both rounds achieved a 100% expert response rate, with an authority coefficient (Cr) of 0.90. The finalized system comprises 6 first-level indicators, 17 second-level indicators, and 64 third-level indicators. Conclusion: The human-machine collaborative teaching-based standardized training system demonstrates scientific rigor, innovation, and practicality, offering a valuable reference for healthcare institutions to implement standardized training for newly recruited nurses.
文章引用:陈伟, 张爱娟, 陈逸飞. 人机协同教学模式下新入职护士规范化培训体系的构建[J]. 护理学, 2025, 14(6): 932-938. https://doi.org/10.12677/ns.2025.146125

参考文献

[1] 国家卫生健康委员会. 全国护理事业发展规划(2021-2025年) [J]. 中国护理管理, 2022, 22(6): 801-804.
[2] 李秀, 陆军, 牛佳丽. GenAI赋能的人机双师协同教学研究——基于清华大学计算机基础课程的案例分析[J]. 现代教育技术, 2025, 35(3): 34-43.
[3] 庞津, 王博巧. 基于案例在线协作教学的医学教育人机混合智能设计研究[J]. 继续医学教育, 2024, 38(7): 162-165.
[4] 姚萍萍, 史绪生, 姜勇, 等. 新入职本科规范化培训护士护理信息能力评价指标体系的构建[J]. 护理研究, 2024, 38(4): 604-608.
[5] 何茂章, 王姝妹, 丁瑞培, 等. 基于新医科与AI技术融合的医学教学模式探讨[J]. 湘南学院学报(医学版), 2024, 26(3): 63-66.
[6] 陈玲, 蒋雨枫. 5G + AI技术赋能医学本科教学改革的相关探索[J]. 临床医学研究与实践, 2024, 9(11): 168-171, 189.
[7] 汪秀衡, 胡恒境. AI医疗背景下医学人才培养改革的探索和思考[J]. 科教文汇(下旬刊), 2021(36): 123-125.