Developing Artificial Intelligence (AI) education in K-12 contexts, i.e., teaching students about AI, is critical to promote students' AI literacy. However, the state-of-the-art of AI education is not clear enough. To this end, this study reviewed 45 high-quality empirical studies on K-12 AI education over the past decade from both research and instruction perspectives. Regarding the research design, this study revealed the relationship between publication year, sample size, learning stage, educational setting, research method, research focus and duration. Regarding the instruction design, this study revealed the relationship between learning stage, pedagogical strategy, learning tool, learning activity, learning content, assessment method and learning effect. Besides, this study also derived recommendations for research (i.e., time allocation, samples selection, longitudinal design, rigorous methodology and technical democracy) and instruction (i.e., group learning, authentic context, teacher involvement, triangular evidence and learning scaffolding). Overall, the main findings indicate that K-12 AI education has the potential to develop students’ AI literacy, which contains AI knowledge, AI affectivity, and AI thinking. However, deficiencies in research and instructional design still remain, including short durations, small sample sizes, non-standardized research methods, lack of long-term and cross-age AI curriculum, etc. This study also discussed several critical topics for future research and instruction.

中文翻译：

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关于教育工作者如何在 K-12 教育中教授 AI 的系统评价


在 K-12 环境中发展人工智能 （AI） 教育，即向学生传授 AI 知识，对于提高学生的 AI 素养至关重要。然而，人工智能教育的最新技术还不够清楚。为此，本研究从研究和教学的角度回顾了过去十年中 45 项关于 K-12 人工智能教育的高质量实证研究。在研究设计方面，本研究揭示了出版年份、样本量、学习阶段、教育环境、研究方法、研究重点和持续时间之间的关系。在教学设计方面，本研究揭示了学习阶段、教学策略、学习工具、学习活动、学习内容、评估方法和学习效果之间的关系。此外，本研究还得出了研究 （即时间分配、样本选择、纵向设计、严格的方法和技术民主） 和教学 （即小组学习、真实背景、教师参与、三角证据和学习支架） 的建议。总体而言，主要研究结果表明，K-12 AI 教育有可能培养学生的 AI 素养，其中包括 AI 知识、AI 情感和 AI 思维。然而，研究和教学设计仍然存在不足，包括持续时间短、样本量小、研究方法不标准化、缺乏长期和跨年龄的人工智能课程等。本研究还讨论了未来研究和教学的几个关键主题。