In the next section (Sample of Adopters) I present 20 Humanities, Social Science, and Arts courses found at undergraduate and secondary level in the US and UK that have been designed to teach and apply computational data tools and methods using Jupyter notebooks. 8 computational data practices
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Introducing new or updating existing tools and methods taught in these educational programs for cutting-edge computational data resources has already been shown to be both feasible and impactful for both instructors and students.
Moreover, in many of these implementations Jupyter notebooks have been a key factor in enabling several valuable outcomes.
To summarise the modern tools and methods facilitated by Jupyter notebook as an educational technology, I have created additional data to show which of 8 computational data practices each course uses Jupyter notebooks to help teach.
User stories from instructors and students of certain courses in the dataset are shared, demonstrating the impactful outcomes that are achievable through modernising Humanities, Social Science, and Arts education, and attributed to the use of Jupyter notebooks.
The article concludes with recommendations for others to consider modernising their curricula to achieve similar outcomes, and to consider using Jupyter notebooks as a key enabler.

However, the user stories show that there are specific characteristics of Jupyter notebooks that make them the preferred platform for the use-cases being examined in this article.