Use of notebooks for cartography teaching

Interactive computational notebooks are browser-based tools that support shared workflows, coding, data, and visualisations. The have become popular quickly in recent years, especially Jupyter, which originally was focussed on the Python language. In 2018, the javascipt-based notebook system Observable was launched. This is based on the visualisation library D3.js, popular with cartographers because of its excellent support for spatial visualisations.

Among others, Camara et al (2021) have shown that by using notebooks it is possible to perform spatial visualisation and analysis in a research environment in an open way, with the advantage of allowing the monitoring and improvement of the code simultaneously by the team involved. Furthermore, the notebooks reinforce the open science and the principles for digital objects: Findable, Accessible, Interoperable, Reusable (FAIR), always aiming the reproducibility and interoperability.
Notebooks are also used in educational settings, also outside the obvious field of programming courses.

For this research, we propose you investigate the potential of notebooks for cartographic education. Next to literature research into Cartography Education methods, you could for example construct specific teaching modules using Observable, and investigate their effectiveness compared to more traditional methods.