Machine learning for middle schoolers: Learning through data-driven design

Abstract

Abstract An entire generation of children is growing up with machine learning (ML) systems that are greatly disrupting job markets as well as changing people’s everyday lives. Yet, that development and its societal effects have been given minor attention in computing education in schools, which mainly focuses on rule-based programming. This article presents a pedagogical framework for supporting middle schoolers to become co-designers and makers of their own machine learning applications. It presents a case study conducted in the 6th grade of a Finnish elementary school and analyses students’ (N=34) evolving ML ideas and explanations. Data consists of a children’s artwork, students’ design ideas and co-designed applications, and structured group interviews organised at the end of the ML project. The qualitative content analysis revealed how hands-on exploration with ML-based technologies supported students in developing various kinds of design ideas that harnessed face recognition, gestures, or voice recognition for solving real-life problems. The results of the study further indicated that co-designing ML applications provided a promising entry point for students to develop their conceptual understanding of ML principles, its workflows, and its role in their everyday practices. The article concludes with a discussion on how to support students to become innovators and software designers in the age of machine learning.