Exploring Generative Models with Middle School Students
Exploring Generative Models with Middle School Students
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DOI：
10.1145/3411764.3445226
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发表时间：
2021-05
期刊：
影响因子：
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通讯作者：
Safinah Ali;Daniella DiPaola;Irene A. Lee;Jenna Hong;C. Breazeal
中科院分区：
文献类型：
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作者：
Safinah Ali;Daniella DiPaola;Irene A. Lee;Jenna Hong;C. Breazeal
生成模型的应用，如生成对抗网络（GAN），已经进入了儿童经常与之互动的社交媒体平台。虽然GAN与儿童相关的道德影响有关，例如Deepfakes的产生，但在教育中学生有关生成AI方面的努力微不足道。在这项工作中，我们为年轻学习者提供了一个生成模型学习轨迹（LT），教育材料和互动活动，重点是GAN，机器生成媒体的创建和应用及其伦理影响。这些活动在四个在线讲习班上展开，有72名学生（5-9年级）参加。我们发现，这些材料使儿童能够了解生成模型是什么，它们的技术组成部分和潜在应用，以及好处和危害，同时反思它们的伦理含义。从我们的研究结果中学习，我们提出了一个改进的学习轨迹复杂的社会技术系统。
Applications of generative models such as Generative Adversarial Networks (GANs) have made their way to social media platforms that children frequently interact with. While GANs are associated with ethical implications pertaining to children, such as the generation of Deepfakes, there are negligible efforts to educate middle school children about generative AI. In this work, we present a generative models learning trajectory (LT), educational materials, and interactive activities for young learners with a focus on GANs, creation and application of machine-generated media, and its ethical implications. The activities were deployed in four online workshops with 72 students (grades 5-9). We found that these materials enabled children to gain an understanding of what generative models are, their technical components and potential applications, and benefits and harms, while reflecting on their ethical implications. Learning from our findings, we propose an improved learning trajectory for complex socio-technical systems.