数字化改头换面

Boyd Britton, Carmen Vallis
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引用次数: 0

摘要

合成媒体和人工智能生成的化身的快速发展和普及,给高等教育带来了挑战和机遇。越来越多的教育机构必须驾驭复杂的伦理和教学考虑因素,并适应最新的人工智能技术(Siemens 等人,2022 年)。教育领域迫切需要伦理和教学原则来指导人工智能的使用(Bozkurt 等人,2021 年)。 在本演讲中,我们将通过一个具体的案例研究,分享一个实用的视角:开发和实施一个大规模的互动商业模块,该模块的特色是由人工智能生成的 "客座讲师"。 人工智能生成的视频内容以及其他在线活动,旨在激发对人工智能在商业中的伦理影响的批判性思考和讨论。目前,该项目已进入第二次迭代,是对合成媒体在 700 多名学生中呈现教育概念的一次重要尝试和评估。 在开发和实施这种学习媒体的过程中,出现了一些基本的伦理和教学问题。例如,教育者在制作内容时所采用的流程和工具的透明度如何(Pataranutaporn 等人,2021 年)?在录制的视频中,人的存在何时会增加价值,是在教学意义上还是在寄生社会意义上(Beege 等人,2019 年)?哪些形式的学习可能从视频内容自动化中受益(或不受益)(Li 等人,2016 年)?基于焦点小组和视频分析的评估数据,我们探讨了这些问题以及合成媒体的潜在能力和局限性。我们还反思了创建项目所使用的工具和技术,以及教育机构在传统制作生态系统中寻求建立人工智能内容创作能力的意义。 我们还探讨了教育媒体中人工智能的新兴类型,以帮助教育工作者根据学习目的和教学模式进行教学设计。最后,我们讨论了学生的反馈如何为学习媒体的设计、制作和交付提供信息,以及学生共同创造和代理的未来方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digital facelift
The rapid development and proliferation of synthetic media and AI-generated avatars present both challenges and opportunities for higher education. Increasingly, educational institutions must navigate complex ethical and pedagogical considerations, as well as adapt to the latest AI technologies (Siemens et al., 2022). Ethical and pedagogical principles to guide AI use are urgently needed in education (Bozkurt et al., 2021).   In this presentation, we share a practical perspective, framed by a specific case-study: the development and implementation of a large-scale, interactive business module featuring AI-generated ‘Guest Lecturers’ The AI-generated video content, along with other online activities, were designed to stimulate critical reflection and discussion about the ethical implications of AI in business. Now in its second iteration, the project represents a significant trial and evaluation of synthetic media to present educational concepts in a cohort of over 700 students.   Fundamental ethical and pedagogical questions surfaced during the development and implementation of this learning media. How transparent should educators be about the processes and tools they adopt in producing content, for example (Pataranutaporn et al., 2021)? When does human presence add value in recorded video, be it in a pedagogical or parasocial sense (Beege et al., 2019)? And what forms of learning might benefit (or not) from automating video content (Li et al., 2016)? Based on evaluation data from focus groups and video analytics, we explore these questions and the potential affordances and limitations of synthetic media. We also reflect on the tools and techniques that were used to create the project, and implications for educational institutions as they seek to build capacity for AI content creation within traditional production ecosystems.   An emergent typology for AI in educational media is explored, to help educators design for teaching and learning based on learning purposes and modes of delivery. Finally, we discuss how student feedback might inform the design, production and delivery of learning media, and future directions for student co-creation and agency.
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