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On the basis of these youth texts – produced within our participatory research at YR Media, a national STEAM learning center and platform for emerging BIPOC content creators – we developed the conceptual framework presented here: Humanizing Data Expression (HDE). The key role of expression in HDE distinguishes the human from the machine through the lens of storytelling. Analysis of this corpus (podcasts, web‐based interactives, videos, radio features, online posts, social media assets) revealed four literacy practices of YR Media authors as they made sense of AI: (1) contextualize: try out AI‐powered features, reveal how it works; (2) unveil authorship: introduce AI creators and processes; (3) grapple: explore tensions and paradoxes; (4) play: hack, mess with, outsmart, exaggerate AI. 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引用次数: 0
摘要
飞速发展的科技进步提出了新的问题:是什么让我们成为独特的人类?随着数据和生成性人工智能变得越来越强大,学习、教学、创造、创造意义和表达自己意味着什么,即使机器被训练来为我们完成这些任务?与年轻人一起,在扫盲和媒体教育的背景下,我们迎接这一时刻,拓宽我们的社会想象力。从2019年到2023年,我们与14-25岁的记者合作,建立了一个由30多篇多模态作品组成的语料库,这些作品是用人工智能和/或有关人工智能的内容创作的,受众数以百万计。YR Media 是一个国家 STEAM 学习中心,也是新兴 BIPOC 内容创作者的平台,我们在 YR Media 的参与式研究中制作了这些青少年文本,在此基础上,我们制定了本文介绍的概念框架:人性化数据表达 (HDE)。在 HDE 中,表达的关键作用是通过讲故事的视角将人与机器区分开来。对这一语料库(播客、基于网络的互动、视频、广播专题、在线帖子、社交媒体资产)的分析揭示了 YR Media 作者在理解人工智能时的四种素养实践:(1) 情境化:尝试人工智能驱动的功能,揭示其工作原理;(2) 揭开作者身份:介绍人工智能的创造者和过程;(3) 争夺:探索紧张关系和悖论;(4) 游戏:黑客、捣乱、智胜、夸大人工智能。从这些见解中,我们最后提出了HDE作为人工智能素养学习和教学框架的意义,包括它在批判性地改变学校、教学和教师教育的数据素养实践和教学法方面的潜力。
“Gotta Love Some Human Connection”: Humanizing Data Expression in an Age of AI
Rapidly developing technological advances have raised new questions about what makes us uniquely human. As data and generative AI become more powerful, what does it mean to learn, teach, create, make meaning, and express ourselves, even as machines are trained to take care of these tasks for us? With youth, and in the context of literacy and media education, we embrace this moment to broaden our social imaginations. Our collaboration with journalists ages 14–25 from 2019 to 2023 has yielded a corpus of over 30 multimodal compositions constructed with and/or about AI reaching audiences in the millions. On the basis of these youth texts – produced within our participatory research at YR Media, a national STEAM learning center and platform for emerging BIPOC content creators – we developed the conceptual framework presented here: Humanizing Data Expression (HDE). The key role of expression in HDE distinguishes the human from the machine through the lens of storytelling. Analysis of this corpus (podcasts, web‐based interactives, videos, radio features, online posts, social media assets) revealed four literacy practices of YR Media authors as they made sense of AI: (1) contextualize: try out AI‐powered features, reveal how it works; (2) unveil authorship: introduce AI creators and processes; (3) grapple: explore tensions and paradoxes; (4) play: hack, mess with, outsmart, exaggerate AI. From these insights, we end with implications of HDE as a framework for learning and teaching AI literacy, including its potential for critically transforming data literacy practice and pedagogy across schools, teaching, and teacher education.
期刊介绍:
For more than 40 years, Reading Research Quarterly has been essential reading for those committed to scholarship on literacy among learners of all ages. The leading research journal in the field, each issue of RRQ includes •Reports of important studies •Multidisciplinary research •Various modes of investigation •Diverse viewpoints on literacy practices, teaching, and learning