arXiv:2502.00567cs.CYcs.AI2025-02中稿 · IEEE EDUCON2025被引 5

通过实地研究揭示职场中GenAI的差异化使用,为教育培养人才提供依据。

Lessons for GenAI Literacy From a Field Study of Human-GenAI Augmentation in the Workplace

  • 对比产品、工程、内容三类岗位的GenAI使用方式
  • 发现技术应用程度与用户计算知识水平差异显著
  • 建议按岗位需求分层设计GenAI教学内容

生成式人工智能(GenAI)正日益融入科技行业及多个领域的日常工作。为更好准备学生应对未来职场,需深入理解专业人士在实际工作中如何使用GenAI。本研究通过实地调查,比较产品开发、软件工程和数字内容创作三类职能中GenAI的应用情况,采用人类增强视角,聚焦人类认知,探讨三个问题:GenAI如何增强工作实践;从业者掌握哪些关键知识及其学习方式;对未来人才培养有何启示。研究发现,不同行业中GenAI使用存在显著差异:部分领域已采用微调模型进行跨域部署,实现高度技术化应用;另一些领域仅使用现成工具生成内容。这表明所需掌握的GenAI知识深度和背景要求各不相同。教学方面,应根据岗位特点分层融入GenAI相关内容。对教师而言,也需关注技术进展,了解学生作为早期使用者已在学习中主动运用GenAI进行辅助。

原文摘要 · Abstract (English)

Generative artificial intelligence (GenAI) is increasingly becoming a part of work practices across the technology industry and being used across a range of industries. This has necessitated the need to better understand how GenAI is being used by professionals in the field so that we can better prepare students for the workforce. An improved understanding of the use of GenAI in practice can help provide guidance on the design of GenAI literacy efforts including how to integrate it within courses and curriculum, what aspects of GenAI to teach, and even how to teach it. This paper presents a field study that compares the use of GenAI across three different functions - product development, software engineering, and digital content creation - to identify how GenAI is currently being used in the industry. This study takes a human augmentation approach with a focus on human cognition and addresses three research questions: how is GenAI augmenting work practices; what knowledge is important and how are workers learning; and what are the implications for training the future workforce. Findings show a wide variance in the use of GenAI and in the level of computing knowledge of users. In some industries GenAI is being used in a highly technical manner with deployment of fine-tuned models across domains. Whereas in others, only off-the-shelf applications are being used for generating content. This means that the need for what to know about GenAI varies, and so does the background knowledge needed to utilize it. For the purposes of teaching and learning, our findings indicated that different levels of GenAI understanding needs to be integrated into courses. From a faculty perspective, the work has implications for training faculty so that they are aware of the advances and how students are possibly, as early adopters, already using GenAI to augment their learning practices.

GenAI应用职场教育教学设计

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