拥抱一个新的前沿:护理教育中的生成人工智能
Stacey A Hobbick1, Sandra D Shapiro2, Deirdre Shoemake3
1About the Authors Stacey Hobbick, DNP, MSN-Ed, AMB-BC, MEDSURG-BC, CNE, is an assistant professor of clinical nursing, Oregon Health & Science University, Portland, Oregon.
Nursing education perspectives
|February 6, 2026
概括
在护理教育中整合生成性人工智能 (AI) 提高了学习资源和工作流效率. 学生的反证实了课程材料的改进,解决了对未来医疗保健需求的准确性和道德性AI使用的问题.
科学领域:
- 护理教育 技术 技术
- 医疗保健中的人工智能
- 教育心理学教育心理学
背景情况:
- 传统的护理教育在适应不断变化的医疗保健需求方面面临挑战.
- 越来越需要创新的教育工具来增强学生的学习和临床准备.
- 生成型人工智能 (AI) 为解决这些教育差距提供了一个新的机会.
研究的目的:
- 探索将生成人工智能集成到预授权学士学位护理课程中的教育影响.
- 评估人工智能增强资源对护理教育和工作流效率的影响.
- 评估学生对人工智能集成课程材料的有效性和调整的反.
主要方法:
- 在学士学位护理课程中实施生成性AI工具.
- 收集和分析有关AI增强学习资源的学生反.
- 讨论与人工智能生成的教育内容相关的准确性和伦理考虑.
主要成果:
- 人工智能增强的资源在弥合护理教育差距方面表现出有效性.
- 学生的反表明,提高了课程材料的可读性和对齐性.
- 该研究涉及AI生成内容的准确性和伦理考虑的关键方面.
结论:
- 生成性人工智能有可能通过适应性学习环境显著提高护理教育.
- 整合人工智能为护理学生准备未来的医疗保健环境,强调预防性护理和健康.
- 人工智能工具可以彻底改变护理教学,提高教育成果和工作流效率.
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