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- W4376311907 abstract "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." @default.
- W4376311907 created "2023-05-13" @default.
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- W4376311907 date "2023-05-10" @default.
- W4376311907 modified "2023-09-28" @default.
- W4376311907 title "Data, Trees, and Forests -- Decision Tree Learning in K-12 Education" @default.
- W4376311907 doi "https://doi.org/10.48550/arxiv.2305.06442" @default.
- W4376311907 hasPublicationYear "2023" @default.
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