TEACHING AND LEARNING DATA-DRIVEN MACHINE LEARNING WITH EDUCATIONALLY DESIGNED JUPYTER NOTEBOOKS

This study examines modelling with machine learning. In the context of a yearlong data science course, explores how upper secondary students apply learning Jupyter Notebooks and document process as computational essay incorporating different steps CRISP-DM cycle. The students’ work is based on teaching module about decision trees in worked example such process. outlines performance carrying out technically reasoning bias data, preparation steps, application context, resulting model. Furthermore, theoretical backgrounds are presented.