Department of Biological and Biomedical Sciences, Aga Khan University, Karachi 74800, Pakistan.
Medical Oncology, Shaukat Khanum Memorial Cancer Hospital and Research Center, Lahore 54000, Pakistan.
Postgrad Med J. 2024 Nov 22;100(1190):959-967. doi: 10.1093/postmj/qgae088.
Traditional assessments often lack flexibility, personalized feedback, real-world applicability, and the ability to measure skills beyond rote memorization. These may not adequately accommodate diverse learning styles and preferences, nor do they always foster critical thinking or creativity. The inclusion of Artificial Intelligence (AI), especially Generative Pre-trained Transformers, in medical education marks a significant shift, offering both exciting opportunities and notable challenges for authentic assessment practices. Various fields, including anatomy, physiology, pharmacy, dentistry, and pathology, are anticipated to employ the metaverse for authentic assessments increasingly. This innovative approach will likely enable students to engage in immersive, project-based learning experiences, facilitating interdisciplinary collaboration and providing a platform for real-world application of knowledge and skills.
This commentary paper explores how AI, authentic assessment, and Student-as-Partners (SaP) methodologies can work together to reshape assessment practices in medical education.
The paper provides practical insights into effectively utilizing AI tools to create authentic assessments, offering educators actionable guidance to enhance their teaching practices. It also addresses the challenges and ethical considerations inherent in implementing AI-driven assessments, emphasizing the need for responsible and inclusive practices within medical education. Advocating for a collaborative approach between AI and SaP methodologies, the commentary proposes a robust plan to ensure ethical use while upholding academic integrity.
Through navigating emerging assessment paradigms and promoting genuine evaluation of medical knowledge and proficiency, this collaborative effort aims to elevate the quality of medical education and better prepare learners for the complexities of clinical practice.
传统评估往往缺乏灵活性、个性化反馈、现实适用性以及衡量除死记硬背之外技能的能力。这些可能无法充分适应多样化的学习风格和偏好，也不一定能培养批判性思维或创造力。人工智能（AI），特别是生成式预训练转换器在医学教育中的应用标志着一个重大转变，为真实评估实践带来了令人兴奋的机遇和显著的挑战。包括解剖学、生理学、药学、牙科学和病理学在内的各个领域预计将越来越多地在真实评估中使用元宇宙。这种创新方法可能使学生能够参与沉浸式、基于项目的学习体验，促进跨学科合作，并为知识和技能的实际应用提供平台。
本文探讨了 AI、真实评估和学生作为伙伴（SaP）方法如何协同作用，重塑医学教育中的评估实践。
本文提供了有效利用 AI 工具创建真实评估的实用见解，为教育工作者提供了增强教学实践的可行指导。它还解决了在实施 AI 驱动评估中固有的挑战和道德考虑因素，强调了在医学教育中需要负责任和包容的实践。本文提倡 AI 和 SaP 方法之间的协作方法，提出了一个稳健的计划，以确保在维护学术诚信的同时进行道德使用。
通过探索新兴的评估范式和促进对医学知识和能力的真实评估，这项协作努力旨在提高医学教育的质量，并更好地为学习者在临床实践的复杂性做好准备。
