A systematic review of AI literacy conceptualization, constructs, and implementation and assessment efforts (2019–2023)

IF 4.1 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers and Education Open Pub Date : 2024-03-31 DOI:10.1016/j.caeo.2024.100173
Omaima Almatrafi , Aditya Johri , Hyuna Lee
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Abstract

The explosion of AI across all facets of society has given rise to the need for AI education across domains and levels. AI literacy has become an important concept in the current technological landscape, emphasizing the need for individuals to acquire the necessary knowledge and skills to engage with AI systems. This systematic review examined 47 articles published between 2019 and 2023, focusing on recent work to capture new insights and initiatives given the burgeoning of the literature on this topic. In the initial stage, we explored the dataset to identify the themes covered by the selected papers and the target population for AI literacy efforts. We identified that the articles broadly contributed to one of the following themes: a) conceptualizing AI literacy, b) prompting AI literacy efforts, and c) developing AI literacy assessment instruments. We also found that a range of populations, from pre-K students to adults in the workforce, were targeted. In the second stage, we conducted a thorough content analysis to synthesize six key constructs of AI literacy: Recognize, Know and Understand, Use and Apply, Evaluate, Create, and Navigate Ethically. We then applied this framework to categorize a range of empirical studies and identify the prevalence of each construct across the studies. We subsequently review assessment instruments developed for AI literacy and discuss them. The findings of this systematic review are relevant for formal education and workforce preparation and advancement, empowering individuals to leverage AI and drive innovation.

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对人工智能素养的概念化、构建、实施和评估工作进行系统审查(2019-2023 年)
人工智能在社会各方面的蓬勃发展,催生了跨领域、跨层次的人工智能教育需求。人工智能素养已成为当前技术领域的一个重要概念,强调个人需要掌握必要的知识和技能,以便与人工智能系统打交道。本系统性综述研究了 2019 年至 2023 年间发表的 47 篇文章,重点关注近期的工作,以便在有关该主题的文献蓬勃发展的情况下捕捉新的见解和举措。在初始阶段,我们对数据集进行了探索,以确定所选论文涉及的主题以及人工智能扫盲工作的目标人群。我们发现这些文章广泛涉及以下主题之一:a) 人工智能扫盲概念化,b) 促进人工智能扫盲工作,c) 开发人工智能扫盲评估工具。我们还发现,从学前班学生到劳动力中的成年人等一系列人群都是研究对象。在第二阶段,我们进行了全面的内容分析,归纳出了人工智能扫盲的六个关键概念:认识、了解和理解、使用和应用、评估、创造和道德导航。然后,我们运用这一框架对一系列实证研究进行了分类,并确定了各研究中每种构建的普遍程度。随后,我们回顾了针对人工智能素养开发的评估工具,并对其进行了讨论。本系统性综述的研究结果与正规教育、劳动力准备和晋升息息相关,可增强个人利用人工智能和推动创新的能力。
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