为生成式人工智能调整评估/尽管如此

Jason Lodge, Michael Henderson, Christine Slade, Chris Deneen
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摘要

生成式人工智能(AI)给高等教育的既定评估实践带来了巨大压力。这些新技术可以生成论文和实验报告等关键工件,而这些工件通常被用来推断学生的学习状况。本小组报告了澳大利亚一个全国性论坛的成果,该论坛旨在制定一套指导原则,以应对生成式人工智能改变评估格局的方式。这包括重新思考我们的评估内容;我们如何确保学生的作业是他们自己的;我们如何通过使用人工智能促进学习;我们如何通过评估培养适当的数字素养;以及我们如何培养人类在以人工智能为媒介的世界中工作的能力。在研讨会成果的基础上,专家小组将深入探讨一些关键挑战,以及如何将指导意见应用于高等教育的各个领域。
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Adapting assessment for/despite generative artificial intelligence
Generative artificial intelligence (AI) has put significant pressure on established assessment practices in tertiary education. These new technologies can produce key artifacts such as essays and laboratory reports that are routinely used to infer where students are in their learning. This panel reports on the outcomes of an Australian national forum to develop a set of guiding principles in response to the ways generative AI is changing the landscape of assessment. This includes rethinking what we assess; how we assure students’ work is their own; how we promote learning through the use of gen AI; how we build appropriate digital literacies through assessment; and how we build human capabilities for working in an AI-mediated world. Building on the output of the workshop, the panel will delve into some of the key challenges and how the guidance can be applied across contexts in tertiary education.
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Governance of artificial intelligence and data in Australasian higher education: A snapshot of policy and practice Learning design principles that cultivate future-oriented students It’s the vibe – Course environment and the intersection of environmental psychology and learner experience design Adapting assessment for/despite generative artificial intelligence Learning analytics with iLearn Insights
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