Co-Designing Machine Learning Apps in K–12 With Primary School Children

Abstract

Artificial intelligence and machine learning are making their ways rapidly to K-12 education. Google Teachable Machine, powered by convolutional neural networks, provides an easy-to-use yet powerful tool for classification tasks. We conducted a series of co-design workshops with primary school children, where they explored and designed their own machine learning powered applications with Google Teachable Machine. Our results show that Google Teachable Machine is a feasible tool for K-12 education. The trained machine learning models are lightweight and computationally efficient, and the applications are usable even with low-end mobile devices. The students and teachers appreciated the multidisciplinary and inclusive workshop, which supports development of transversal competencies in accordance to the national primary school curriculum.