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Explorative and Embodied Approaches to Teaching Machine Learning: From Research to Practice

About the project

This project explores how HCI research into embodied and explorative approaches to teaching machine learning can impact teaching practices in primary and secondary education classrooms. This includes applying research methods that engage with existing organizational infrastructures in the education sector and the development of research toolkits that integrate with teachers’ practices and the limitations of the classroom context. We identify findings and experiences from our previous studies on machine learning teaching and develop them into applicable, scalable educational design approaches. To make these approaches available for educators, we build scalable tools and high-quality educational materials, which we distribute through existing platforms and channels. We do this in collaboration with educational organizations such as DR Lær and Micro:bit Educational Foundation.

Project contribution

In this project, we have matured the educational tool for teaching machine learning: ml-machine.org. The tool is publicly available for educators, and the code base is open-sourced to researchers and educational developers. We have developed educational material in collaboration with DR about artificial intelligence and social media, targeting 7th grade. Further, Micro:bit Educational Foundation and BBC have developed educational material around the tool where UK primary school students collect data in playgrounds, utilizing and learning about machine learning models.

Further, ml-machine.org is used in workshops by Center For Undervisningsmidler, Verdens Bedste Robotby, the SHAPE project at Aarhus University as well as other educational organizations.

Last, the tool is featured in the Royal Institution’s Christmas Lectures 2023, and the German Calliope organization is working on a version for their hardware platform targeting German students.

We use the project to explore how HCI research into educational tools for teaching digital technologies can integrate into existing educational infrastructures and have a substantial impact on teaching practices.





Funding partner

IT-Vest & VILLUM FONDEN (#28831)

Research areas


Publication category