Machine Learning for All – Introducing Machine Learning in K-12
Machine Learning for All – Introducing Machine Learning in K-12
复制标题
全民机器学习——在 K-12 中引入机器学习
DOI：
10.31235/osf.io/wj5ne
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
J. Hauck
中科院分区：
文献类型：
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作者：
Christiane Gresse von Wangenheim;L. S. Marques;J. Hauck
尽管机器学习（ML）如今已融入我们生活的各个方面，但很少有人了解其背后的技术。这就提出了新的挑战，即早期扩展计算教育，包括ML概念，以帮助学生了解其潜力和局限性，并使他们成为智能解决方案的创造者。因此，我们开发了一门入门课程来教授基本的ML概念，例如神经网络的基础知识，学习以及与K-12人工智能指南一致的限制和伦理问题。并通过引导学生使用谷歌教学机开发回收垃圾的第一个图像识别模型，教授这些概念的应用。为了促进机器学习教育，互动式课程以巴西葡萄牙语在线提供，可作为课外课程或跨学科方式作为涵盖回收主题的科学课程的一部分。
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 on including ML concepts in order to help students to understand its potential and limits and empowering them to become creators of intelligent solutions. Therefore, we developed an introductory course to teach basic ML concepts, such as fundamentals of neural networks, learning as well as limitations and ethical concerns in alignment with the K-12 Guidelines for Artificial Intelligence. It also teaches the application of these concepts, by guiding the students to develop a first image recognition model of recycling trash using Google Teachable Machine. In order to promote ML education, the interactive course is available online in Brazilian Portuguese to be used as an extracurricular course or in an interdisciplinary way as part of science classes covering recycling topics.