Intercontinental evidence on learners’ differentials in sense-making of machine learning in schools

Abstract

Given the importance of machine learning for K-12 levels, finding out ways to communicate the concept to students such that it will be less intimidating is necessary. This will help to demystify machine learning for students. Drawing on qualitative methodology approach, this study aims to explore how to teach machine learning in K-12 context using middle school students’ samples in Nigeria, Finland, and United States. Considering the cross-contextual approach and the study aim, this research will be a valuable addition to the limited evidence that support differentials in students learning of machine learning technology across culture and background. The study outcome will be an indispensable resource for addressing how the uniqueness of each contexts can be leveraged on to best introduce machine learning to schools.