Ken Masters, Heather MacNeil, Jennifer Benjamin, Tamara Carver, Kataryna Nemethy, Sofia Valanci-Aroesty, David C M Taylor, Brent Thoma, Thomas Thesen
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引用次数: 0
Abstract
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.
期刊介绍：
Medical Teacher provides accounts of new teaching methods, guidance on structuring courses and assessing achievement, and serves as a forum for communication between medical teachers and those involved in general education. In particular, the journal recognizes the problems teachers have in keeping up-to-date with the developments in educational methods that lead to more effective teaching and learning at a time when the content of the curriculum—from medical procedures to policy changes in health care provision—is also changing. The journal features reports of innovation and research in medical education, case studies, survey articles, practical guidelines, reviews of current literature and book reviews. All articles are peer reviewed.
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