How‐To Strategies for Integrating Generative Artificial Intelligence ( GenAI ) Into Pharmacy Education Teaching and Learning Activities

药店 形成性评价 工作流程 计算机科学 鉴定(生物学) 医学教育 医疗保健 生成语法 心理学 药学实习 工程伦理学 知识管理 专业发展 课程 教学方法 教学设计 生成模型 最佳实践 人工智能 服务学习 药剂学 体验式学习 高等教育 委派
作者
Kathryn A. Morbitzer,Jacqueline E. McLaughlin,Kathryn A. Fuller,Xiaotong Li,Zachary R. Noel,Philip T. Rodgers,Christine M. Ruby,Michael Stepanovic,Sandra L. Kane‐Gill
出处
期刊:JACCP: journal of the American College of Clinical Pharmacy [Wiley]
卷期号:9 (7): e70257-e70257
标识
DOI:10.1002/jac5.70257
摘要

Artificial intelligence (AI), including generative artificial intelligence (GenAI), is increasingly being incorporated into health care practice and academic environments, creating an urgent need for pharmacy education programs to prepare learners to engage with these tools responsibly. Accrediting bodies and professional organizations emphasize innovation, digital literacy, and readiness for contemporary practice; however, specific guidance on how GenAI should be integrated into pharmacy education remains limited. As a result, pharmacy educators face uncertainty related to pedagogical alignment, ethical use, assessment integrity, and student reliance on AI-generated outputs. The purpose of this "how-to" guide is to assist pharmacy educators and training program leaders with practical strategies and examples for integrating GenAI into teaching and assessment across pharmacy education. This guide presents foundational principles to support responsible GenAI use, followed by a step-by-step framework that addresses identification of instructional needs, selection of appropriate GenAI modalities, activity design, student preparation for critical AI use, and assessment and refinement of AI-enabled learning activities. Common instructional contexts and applications are illustrated using real-world examples, including clinical reasoning exercises, communication skill development, scalable assessment, scholarly writing support, and formative feedback. Key challenges encountered during GenAI integration are synthesized, including overreliance on AI, inaccurate or biased outputs, variability in AI performance, and workflow considerations for faculty and learners. Specific mitigation strategies and design decisions are provided to support intentional implementation while maintaining academic rigor and professional standards. By focusing on instructional strategies rather than specific tools, this guide offers adaptable recommendations to support pharmacy educators in leveraging GenAI to enhance learning and prepare trainees for AI-enabled pharmacy practice.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
天真的道罡完成签到,获得积分10
1秒前
2秒前
2秒前
所所应助小史在读采纳,获得10
3秒前
3秒前
翁宇轩发布了新的文献求助10
4秒前
4秒前
5秒前
喻安琪完成签到 ,获得积分10
5秒前
顾矜应助cane采纳,获得10
5秒前
6秒前
唯手熟尔发布了新的文献求助10
6秒前
Yanjiakun发布了新的文献求助10
6秒前
7秒前
SciGPT应助嘉欣采纳,获得10
8秒前
nicknick发布了新的文献求助30
8秒前
9秒前
稳重一鸣发布了新的文献求助10
9秒前
JIA完成签到,获得积分10
9秒前
WN发布了新的文献求助10
9秒前
独角戏完成签到,获得积分10
10秒前
10秒前
英俊的铭应助黎明采纳,获得10
11秒前
11秒前
sdfwsdfsd发布了新的文献求助30
12秒前
zimi完成签到,获得积分10
13秒前
13秒前
13秒前
13秒前
15秒前
畜牧笑笑发布了新的文献求助10
15秒前
sunly发布了新的文献求助10
16秒前
真的难找应助习惯过了头采纳,获得10
16秒前
keyanbaicai发布了新的文献求助10
16秒前
rljsrljs完成签到 ,获得积分10
17秒前
dkkkkk完成签到,获得积分10
17秒前
游游游完成签到,获得积分10
19秒前
19秒前
所所应助刻苦的面包采纳,获得10
19秒前
顺利的爆米花完成签到 ,获得积分10
20秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
ズームレンズの光学設計に関する研究 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7296313
求助须知:如何正确求助?哪些是违规求助? 8914502
关于积分的说明 18876219
捐赠科研通 6962433
什么是DOI,文献DOI怎么找? 3210386
关于科研通互助平台的介绍 2379662
邀请新用户注册赠送积分活动 2186743