On Computational Notebooks to Empower Physical Computing Novices

The ever-increasing availability and variety of resources to create physical computing systems keep attracting electronics hobbyists and do-it-yourself enthusiasts. Nevertheless, the prototyping and development of these systems are still challenging to the novices. In this paper, we propose a tool (built on top of the Jupyter computational notebook) as a way for supporting step-by-step assisted learning and knowledge sharing. We extended the Jupyter notebook functionalities and implemented a custom-tailored kernel to seamlessly enable the interaction between the end-user web interface and the Arduino boards. We consider that this approach can effectively support physical computing novices in understanding, writing, and executing the code while empowering them to document and share the development steps they followed.