Abstract. Although Machine Learning (ML) is integrated today into various aspects of our lives, few understand the technology behind it. This presents new challenges to extend computing education early to ML concepts helping students to understand its potential and limits. Thus, in order to obtain an overview of the state of the art on teaching Machine Learning concepts in elementary to high school, we carried out a systematic mapping study. We identified 30 instructional units mostly focusing on ML basics and neural networks. Considering the complexity of ML concepts, several instructional units cover only the most accessible processes, such as data management or present model learning and testing on an abstract level black-boxing some of the underlying ML processes. Results demonstrate that teaching ML in school can increase understanding and interest in this knowledge area as well as contextualize ML concepts through their societal impact.

中文翻译：

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在学校中进行机器学习教学：最新状态的系统映射

摘要。尽管如今机器学习（ML）已集成到我们生活的各个方面，但很少有人了解它背后的技术。这为将计算教育尽早扩展到ML概念提出了新挑战，帮助学生了解ML的潜力和局限性。因此，为了获得从小学到高中的机器学习概念教学的最新发展概况，我们进行了系统的制图研究。我们确定了30个教学单元，主要侧重于ML基础知识和神经网络。考虑到ML概念的复杂性，几个教学单元仅涵盖了最易访问的过程，例如数据管理或抽象模型上的当前模型学习和测试，使一些底层的ML过程被黑盒化。