As a consequence of the increasing influence of machine learning on our lives, everyone needs competencies to understand corresponding phenomena, but also to get involved in shaping our world and making informed decisions regarding the influences on our society. Therefore, in K-12 education, students need to learn about core ideas and principles of machine learning. However, for this target group, achieving all of the aforementioned goals presents an enormous challenge. To this end, we present a teaching concept that combines a playful and accessible unplugged approach focusing on conceptual understanding with empowering students to actively apply machine learning methods and reflect their influence on society, building upon decision tree learning.

翻译：随着机器学习对我们生活的影响日益加深，每个人都需要具备理解相应现象的能力，同时也要参与塑造我们的世界，并就其对社会的影响做出明智的决策。因此，在K-12教育中，学生需要学习机器学习的核心思想和原理。然而，对于这一目标群体而言，实现上述所有目标构成了巨大挑战。为此，我们提出了一种教学理念，它将侧重于概念理解的趣味性和易用性的无计算机教学法，与赋予学生主动应用机器学习方法并反思其社会影响的能力相结合，其基础是决策树学习。