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Why Are We Not Teaching Machine Learning at High School? A Proposal

2018 World Engineering Education Forum - Global Engineering Deans Council (WEEF-GEDC)(2018)

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Abstract
Although there are many online resources for youngsters to start learning about machine learning on their own, a majority of them require solid mathematical or programming background. In addition, there is a lack of material on how to effectively teach machine learning. This paper is motivated by a survey conducted among young students in a technical high-school to inquire on their interest in learning how computers learn. Given the fact that almost every high-school student has heard about artificial intelligence and is curious about it, this article proposes a way to give a friendly introduction to machine learning in the context of a short workshop. Through a series of problem-based activities, students are expected to understand the foundations of what does 'learning' mean for a computer. In addition, through analogies as well as toy and real problems, this short workshop will tackle students' preconceptions, give them an insight of what tools are important in order to deal with this popular topic and address the ethical issues that arise. Moreover, it is desirable that this stimulates students' interest for STEM degrees. Finally, the activities proposed can be easily adapted for an introductory engineering course.
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Key words
machine learning,artificial intelligence,problem-based learning
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