探索人工智能辅助学生作业的前沿领域:挑战、技能与解决方案。
Navigating the frontier of AI-assisted student assignments: challenges, skills, and solutions.
作者信息
Estaphan Suzanne, Kramer David, Witchel Harry J
机构信息
School of Medicine and Psychology, College of Science and Medicine, Australian National University, Canberra, Australia.
Graduate School of Medicine, University of Wollongong, Wollongong, Australia.
出版信息
Adv Physiol Educ. 2025 Sep 1;49(3):633-639. doi: 10.1152/advan.00253.2024. Epub 2025 Apr 25.
The rise of artificial intelligence (AI) is transforming educational practices, particularly in assessment. While AI may support the students in idea generation and summarization of source materials, it also introduces challenges related to content validity, academic integrity, and the development of critical thinking skills. Educators need strategies to navigate these complexities and maintain rigorous, ethical assessments that promote higher order cognitive skills. This article provides practical guidance for educators on designing take-home assessments (e.g. research-based assignments) in the AI era. This guidance was developed through a collaborative, consensus-driven process involving a consortium of three educators with diverse academic backgrounds, career stages, and perspectives on AI in education. Members, holding experience in higher education across the United Kingdom, United States of America, Australia, and Middle East and North Africa regions, brought varied insights into AI's role in education. The team engaged in an iterative process of refining recommendations through biweekly virtual meetings and offline discussions. Four key recommendations are presented ) codeveloping AI literacy among students and educators, ) designing assessments that prioritize process over output, ) validating learning through AI-free assessments, and ) preparing students for AI-enhanced workplaces by developing AI communication skills and promoting human-AI collaboration. These strategies emphasize ethical AI use, personalized feedback, and creativity. By adopting these approaches, educators can balance the benefits and risks of AI in assessments, fostering authentic learning while preparing students for the challenges of an AI-driven world. This paper presents a framework to effectively design take-home assessments in the generative artificial intelligence (AI) era with four key recommendations to navigate the challenges and opportunities posed by generative AI. From codeveloping AI literacy to fostering human-AI collaboration, the strategies empower educators to promote authentic learning, critical thinking, and ethical AI use. Adaptable to various contexts, these insights help prepare students for an AI-driven future while maintaining academic rigor and integrity.
人工智能(AI)的兴起正在改变教育实践,尤其是在评估方面。虽然人工智能可以在学生生成想法和总结源材料方面提供支持,但它也带来了与内容效度、学术诚信以及批判性思维技能发展相关的挑战。教育工作者需要策略来应对这些复杂性,并维持严格、符合道德规范的评估,以促进高阶认知技能的发展。本文为教育工作者在人工智能时代设计带回家完成的评估(例如基于研究的作业)提供了实用指导。该指导是通过一个由三位具有不同学术背景、职业阶段以及对人工智能在教育中看法的教育工作者组成的联盟共同推动、达成共识的过程而制定的。这些成员在英国、美国、澳大利亚以及中东和北非地区的高等教育领域拥有经验,他们对人工智能在教育中的作用有着不同的见解。该团队通过每两周一次的虚拟会议和线下讨论,参与了一个不断完善建议的迭代过程。本文提出了四项关键建议:一是在学生和教育工作者中共同培养人工智能素养;二是设计注重过程而非结果的评估;三是通过无人工智能的评估来验证学习效果;四是通过培养人工智能沟通技能和促进人机协作,让学生为人工智能增强型工作场所做好准备。这些策略强调了人工智能的道德使用、个性化反馈和创造力。通过采用这些方法,教育工作者可以在评估中平衡人工智能的益处和风险,促进真实学习,同时让学生为人工智能驱动的世界所带来的挑战做好准备。本文提出了一个框架,以在生成式人工智能时代有效地设计带回家完成的评估,并给出四项关键建议,以应对生成式人工智能带来的挑战和机遇。从共同培养人工智能素养到促进人机协作,这些策略使教育工作者能够促进真实学习、批判性思维和人工智能的道德使用。这些见解适用于各种情境,有助于让学生为人工智能驱动的未来做好准备,同时保持学术严谨性和诚信。