RPF Seminar: Using the micro:bit to learn about machine learning practices

This seminar will present the research and design rationales behind ml-machine.org — the precursor to micro:bit’s CreateAI. This educational tool lets students build machine learning models with accelerometer data from the micro:bit.

Karl-Emil Bilstrup will show prototypes of tangible interfaces and embodied activities that enable secondary-level students to explore data processes and machine learning practices. He will discuss how these tools can support critical reflections on the ethical design considerations and trade-offs involved in creating data-driven systems and how they can unbox aspects of modern chatbots. Further, he will describe his collaborations with teachers, schools, and other educational organisations, such as the Danish Broadcasting Corporation and the Micro:bit Educational Foundation, to integrate his tools into educational and organisational practices.

Karl-Emil Bilstrup is a postdoctoral computer science researcher and interaction designer at Copenhagen University. He is part of the Center for Computational Thinking and Design at Aarhus University, Denmark, where he did his PhD on designing educational tools for teaching machine learning in secondary education with a Scandinavian focus on sustaining students’ agency in an increasingly digitised and computationalised world. He has contributed to research in embodied interaction for learning and has been a visiting researcher in the Embodied Design Research Laboratory at UC Berkeley. He has collaborated with the Micro:bit Educational Foundation about designing CreateAI, which brings embodied activities with machine learning into classrooms.