Sample of Adopters

# Definition of interdisciplinary HSSA education where Jupyter notebooks used as a tool

The Dataset - Sources, Criteria, Interpretations, Limitations

Through manually searching public data sources (Appendix A) and supplementing with data from my own work I have collated a sample of 20 taught courses relevant to the article's interests from undergraduate and secondary level in the US and UK.
Each course included uses Jupyter to teach computation data tools and methods, which make up a significant proportion of course syllabus, but is unmistakably a means to an end and thus the overall purpose of said technical content is its' application to Humanities, Social Science, and Arts topics. This criteria therefore rules out several Jupyter-based teaching that have either too small-scale computational data focus (such as UC Berkeley courses under the deliberate strategy of initial small-scale Data Science integration \cite{berkeley}), as well as full-scale Data Science courses where computational data practices are the end goal.

Range of Humanities, Social Science, and Arts topics