Masters Ken, MacNeil Heather, Benjamin Jennifer, Carver Tamara, Nemethy Kataryna, Valanci-Aroesty Sofia, Taylor David C M, Thoma Brent, Thesen Thomas
Medical Education and Informatics Department, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Sultanate of Oman.
Department of Medicine, University of Toronto, Toronto, Canada.
Med Teach. 2025 Sep;47(9):1410-1424. doi: 10.1080/0142159X.2024.2445037. Epub 2025 Jan 9.
Health Professions Education (HPE) assessment is being increasingly impacted by Artificial Intelligence (AI), and institutions, educators, and learners are grappling with AI's ever-evolving complexities, dangers, and potential. This AMEE Guide aims to assist all HPE stakeholders by helping them navigate the assessment uncertainty before them. Although the impetus is AI, the Guide grounds its path in pedagogical theory, considers the range of human responses, and then deals with assessment types, challenges, AI roles as tutor and learner, and required competencies. It then discusses the difficult and ethical issues, before ending with considerations for faculty development and the technicalities of AI acknowledgment in assessment. Through this Guide, we aim to allay fears in the face of change and demonstrate possibilities that will allow educators and learners to harness the full potential of AI in HPE assessment.
健康职业教育（HPE）评估正日益受到人工智能（AI）的影响，各机构、教育工作者和学习者都在应对人工智能不断演变的复杂性、风险和潜力。本AMEE指南旨在帮助所有HPE利益相关者应对面前的评估不确定性，从而为他们提供帮助。尽管推动力是人工智能，但该指南以教学理论为基础，考虑了一系列人类反应，然后探讨了评估类型、挑战、人工智能作为导师和学习者的角色以及所需的能力。接着讨论了困难和伦理问题，最后考虑了教师发展以及在评估中认可人工智能的技术细节。通过本指南，我们旨在消除面对变革时的恐惧，并展示各种可能性，使教育工作者和学习者能够在HPE评估中充分发挥人工智能的潜力。
