Artificial intelligence (AI) has been hailed for its potential to revolutionize teaching and learning practices. Undoubtedly, there has been development, but has it transferred to a new pedagogical trend? Indeed, research shows more tools, software, etc., built through AI, but there is still a limited understanding of its pedagogical impact. This review aims to assess whether AI has indeed led to new pedagogical trends in education using a Human Center AI framework. To accomplish this, a systematic review of research on the pedagogical applications of AI in K-12 contexts was conducted, following the PRISMA guidelines. The review involved an inductive coding analysis of a comprehensive search across WoS, Scopus, and EBSBU. From a pool of 3277 publications spanning 2019 to 2023, 183 papers met the inclusion criteria for detailed analysis. Six categories emerged: Behaviorism, Cognitivism, Constructivism, Social Constructivism, Experiential Learning, and Community of Practices. The findings of this research provide a promising perspective on synthesizing the results based on the pedagogical framework that describes AI implementation. While technological advancements have improved AI capabilities, the application of AI in education largely follows the same principles of previous technologies. This research suggests that the failure to transform education through AI stems from a lack of consideration of Gardner's proposed ninth intelligence type—pedagogical intelligence. Furthermore, this paper offers a critical analysis of the HCAI framework and proposes an adaptation called Pedagogical Centered AI (PCAI) for designing and using AI in K-12 education. Final discussions highlight the implications and future perspectives of AI in educational settings.

中文翻译：

---

学校教学中的人工智能：对教学智能的需求


人工智能 (AI) 因其彻底改变教学实践的潜力而受到赞誉。毫无疑问，是有发展，但是否已经转变为新的教学趋势呢？事实上，研究表明有更多的工具、软件等是通过人工智能构建的，但对其教学影响的了解仍然有限。本次审查旨在评估人工智能是否确实使用人类中心人工智能框架引领了教育领域的新教学趋势。为了实现这一目标，根据 PRISMA 指南，对 K-12 背景下人工智能的教学应用研究进行了系统回顾。该评论涉及对 WoS、Scopus 和 EBSBU 的综合搜索进行归纳编码分析。在 2019 年至 2023 年的 3277 篇出版物中，有 183 篇论文符合详细分析的纳入标准。出现了六个类别：行为主义、认知主义、建构主义、社会建构主义、体验式学习和实践社区。这项研究的结果为基于描述人工智能实施的教学框架综合结果提供了一个有前景的视角。虽然技术进步提高了人工智能的能力，但人工智能在教育中的应用在很大程度上遵循了先前技术的相同原理。这项研究表明，通过人工智能改变教育的失败源于缺乏对加德纳提出的第九种智能类型——教育智能的考虑。此外，本文对 HCAI 框架进行了批判性分析，并提出了一种称为以教育为中心的人工智能 (PCAI) 的改编方案，用于在 K-12 教育中设计和使用人工智能。最后的讨论强调了人工智能在教育环境中的影响和未来前景。