在药理学课程中利用基于案例的学习练习来促进药学学生的AI准备
Shankar Munusamy1, Shantanu Rao2, Vanishree Rajagopalan3
1University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, 12850 E. Montview Blvd, Aurora, CO 80045.
American journal of pharmaceutical education
|February 9, 2026
概括
药学学生通过基于案例的学习在药理学中使用人工智能 (AI) 工具获得了显著的信心和元认知技能. 解决AI可靠性和学术完整性是其在药学教育中采用的关键.
科学领域:
- 药房 教育 教育 药房 教育
- 医疗保健中的人工智能
- 发展元认知技能 发展元认知技能
背景情况:
- 药房课程越来越需要新技术的整合.
- 药学学生需要增强的信心和元认知技能,以有效地利用人工智能工具.
- 生成型人工智能为药理学中基于证据的实践带来了机遇和挑战.
研究的目的:
- 提高药学学生在使用人工智能 (AI) 工具时的信心和元认知意识.
- 将生成性AI整合到药理学课程中,以便为AI做好准备.
- 引导学生用基于证据的药物资源对人工智能生成的信息进行三角化.
主要方法:
- 二年级药学学生完成了两个基于案例的药理学作业.
- 学生接受了人工智能工具即时写作培训.
- 人工智能生成的信息与基于证据的药物参考进行了交叉验证.
- 干预前后的调查评估了信心; 一个元认知调查评估了技能.
主要成果:
- 学生对使用人工智能工具的信心显著增加,从64.0%增加到89.4% (p<.001).
- 规划,监测,调试和评估方面的元认知技能有所改善 (74.6%至94.9%).
- 确定的主要障碍是学术完整性问题 (69.5%),可靠性 (52.5%) 和道德问题 (50.8%).
- 学生们对使用人工智能进行概念理解和学习指南生成表示兴趣.
- 建议包括更多的人工智能培训和明确的学术诚信指南.
结论:
- 基于案例的作业有效地培养药学学生的AI能力,信心和元认知技能.
- 解决学术诚信和可靠性问题对于在药学教育中采用人工智能至关重要.
- 未来的药房课程应该包含结构化的AI培训和指导方针.
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