Opportunities and Challenges of Teaching Machine Learning as a Design Material with the micro:bit
Karl-Emil Kjær Bilstrup, Magnus Høholt Kaspersen, Marie-Louise Stisen Kjerstein Sørensen, Marianne Graves Petersen
Abstract
There has been a growing focus on preparing children for navigating a future where digital technologies, such as Machine Learning (ML), are present in both society and personal life. In order to let students explore how ML is embedded into our infrastructure, we designed ml-machine.org, an educational tool for creating ML models with the micro:bit, and incorporating them into interactive systems, thus making ML a design material. Through an in-situ pilot study in an 8th grade classroom we demonstrates that students were able to redesign everyday objects around the possibilities and limitations imposed by ML, but that they struggled to understand more advanced parts of ML such as data representation. Based on these experiences we discuss focus areas for future directions of the tool: Enriching machine learning as a design material; exposing machine learning design practices; addressing the difficult parts.