设计策略为医科大学的基于人工智能的未来学习中心
Yang Xiaowen1, Ding Jingjing2, Wang Biao1
1Nanjing Medical University Library, Nanjing, Jiangsu, China.
BMC medical education
|January 31, 2025
概括
医学院的学生 医学院的学生
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 技术的接受技术的接受
背景情况:
- 研究医学学生采用人工智能 (AI) 工具的情况.
- 确定影响学术环境中人工智能工具接受的关键因素.
研究的目的:
- 为医科大学开发AI集成学习环境提供理论基础和实际建议.
- 了解医学学生持续使用人工智能技术背后的驱动因素.
主要方法:
- 使用结构方程建模 (SEM) 来进行数据分析.
- 整合了技术接受和使用的统一理论 (UTAUT),预期确认理论 (ECT) 和创新传播理论 (IDT).
主要成果:
- 努力期望,促进条件,社会影响力和满意度显著预测继续使用人工智能工具的意图.
- 相对优势影响对人工智能工具的满意度.
- 个人创新能力调节了促进条件,满意度和持续意图之间的关系.
结论:
- 以人工智能为中心的学习中心需要个性化的学习路径和强大的技术支持.
- 促进协作,创新环境和突出工具优势对于人工智能采用至关重要.
- 有效的实施需要解决学生的感知和支持系统.
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