My note: it is NOT about creating masses of programmers and driving the salaries down, as the author claims; it is about fostering a generation, which is technology literate. A doctor, knowing how to code will be a better doctor in the era of IoT; a philosopher knowing how to code will be better in the era of digital humanities.
This course will introduce students to text encoding according to the Text Encoding Initiative (TEI) Guidelines. Why should you care about text encoding or the TEI Guidelines? The creation of digital scholarly texts is a core part of the digital humanities and many digital humanities grants and publications require encoding texts in accordance with the TEI Guidelines. Students in this course will learn about the use-cases for text encoding and get a basic introduction to the principles of scholarly editing before moving on to learning some XML basics and creating a small-scale TEI project using the XML editor oXygen. We will not cover (beyond the very basics) processing TEI, and students interested in learning about XSLT and/or XQuery should turn to the LJA courses offered on those subjects. This course as this course is intended as a follow up to the Introduction to Digital Humanities for Librarians course, but there are no prerequisites, and the course is open to all interested.
– A basic understanding of digital scholarly editing as an academic activity.
– Knowledge of standard TEI elements for encoding poetry and prose.
– Some engagement with more complex encoding practices, such as working with manuscripts.
– An understanding of how librarians have participated in text encoding.
– Deeper engagement with digital humanities practices.
John Russell is the Associate Director of the Center for Humanities and Information at Pennsylvania State University. He has been actively involved in digital humanities projects, primarily related to text encoding, and has taught courses and workshops on digital humanities methods, including “Introduction to Digital Humanities for Librarians.”
In Kentucky, mining veteran Rusty Justice decided that code could replace coal. He cofounded Bit Source, a code shop that builds its workforce by retraining coal miners as programmers. Enthusiasm is sky high: Justice got 950 applications for his first 11 positions. Miners, it turns out, are accustomed to deep focus, team play, and working with complex engineering tech. “Coal miners are really technology workers who get dirty,” Justice says.
The whole problem is rooted in the abuse of the key term, language. In foreign languages the term language refers to “the system of words or signs that people use to express thoughts and feelings to each other” (Merriam-Webster) while in programming languages the term language means “a formal system of signs and symbols including rules for the formation and transformation of admissible expressions“ (Merriam-Webster). To equate foreign languages with programming languages reduces learning a foreign language to the mere acquisition of a set of tokens or words that are semantically and syntactically glued together. It fundamentally ignores the societal, cultural and historical aspects of human languages.