Designed by Katherine Walden // Powered by Jupyter Book
This site hosts instructional materials for the University of Notre Dame's "Code in Context: Computing & the Liberal Arts" course, a newly-designed course offering that combines hands-on introduction to the basic concepts and technologies of computing with critical discussion of the historical, social, and cultural dimensions of computing, data, and digital technology. The work of the course includes discussions of content that foregrounds the cultural, social, and historical dimensions of computing technologies along with exploration and foundational skill building with various computing tools and methods.
The course is part of the College of Arts and Letters Technology & Digital Studies Program.
Folks working in and around digital studies, digital humanities, or other kinds of data literacy spaces may find these resources helpful.
Python's jupyter-book package renders the .md * .ipynb files in this repository as .html files, which are the backbone of the public-facing website.
Those .html files live in the gh-pages branch of this repository.
A few notes on how the repository is structured:
/bookhas.md, &.ipynbfiles, organized in folders/book/_toc.ymlstructures the table of contents that shows up on the left-hand side of site pages/book/_config.ymlsets up key features and functionality for the site/book/datacontains data files
This material is licensed under a CC BY-NC-SA license. This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. If you remix, adapt, or build upon the material, you must license the modified material under identical terms.
Katherine Walden, Code in Context: Computing & the Liberal Arts, Version 1 (2024), DOI PLACEHOLDEr.
Chapter-specific acknowledgements are included in the relevant sections.
The larger course framework draws on the teaching practice and instructional resources of a fabulous group of folks (in no particular order): Dr. Samuel Rebelsky, Dr. Janet Davis, Dr. Liz Rodrigues, Dr. Lindsay K. Mattock, Dr. Miriam Posner, Dr. Anelise Hanson-Shout, Dr. David Eichmann, Megan Adams, Jarren Santos, Ben Chiewphasa.
Making these teaching resource available via Jupyter Book takes inspiration from Melanie Walsh's Introduction to Cultural Analytics & Python textbook.