What this subset matrix is therefore able to illustrate is example interdisciplinary HSSA education where Jupyter notebooks have been adopted as the key pedagogical tool for facilitating the computational data aspects manifested, to some extent, in the real-world.
Specifically, we can use the matrix to pinpoint actual use-cases, within article scope, for Jupyter notebooks, i.e. combination of industry or research-relevant computational data practices paired with humanistic, societal, or artistic purposes to be technically enlivened.
Moreover, many of the notebook use-cases can be seen as novel and pathbreaking, given the stage of education. At UC Berkeley the undergraduates taking Data, Law & Prediction (Index 14) get taught natural language processing techniques, and then perform sentiment analysis to explore the question: "Did the way judges, prosecutors, and witnesses talk about moral culpability change after the Bloody Code was mostly repealed in 1827 (at the leading edge of a wave of legal reform in England)?" \cite{berkeleya}. At Notting Hill & Ealing High School, the Year 10 (9th Grade) students taking my Code Art course (Index 19), after receiving initial instruction of basic vector math were then transfer their understanding to customize the animation for the holiday-themed GIFs they were programming.
Of course, lacking a 'control' against which to compare even just curricula design makes it impossible to infer and attribute the true effect of employing Jupyter notebooks as the pedagogical tool versus available alternatives, for example in terms of feasible content.
It does, however, allow us to start building a picture of the activity of the interdisciplinary HSSA education in scope and the sorts of directions this is heading, for example in terms of computational data upskilling aspirations and technology choices of departments, educational institutions, and relevant stakeholders.
Against this backdrop, the next section provides more conclusive evidence in support of the case for Jupyter notebooks being made by this article, as we gain deeper insight into a handful of the courses in the sample from available user experience data of five instructor, staff, and/or students of the pedagogical benefits they attribute to the use of this technology.