We have been teaching together and leading a research group (English and Computer Science) in various ways for a decade. Here are some papers that more fully describe some of our work.
Boese, E.S., LeBlanc, M.D., and Quinn, B.A. (2017). EngageCSEdu: Making interdisciplinary connections to engage students. ACM Inroads, v8(2), 33-36.
LeBlanc, M.D. (2016). Computing and the Digital Humanities. An NCWIT Teaching Paper: National Center for Women & Information Technology. Published sets of course materials for the “Computing for Poets” course.
LeBlanc, M.D. and Drout, M.D.C. (June 2, 2015). DNA and 普通話 (Mandarin): Bringing introductory programming to the Life Sciences and Digital Humanities. Procedia Computer Science: International Conference on Computational Science, 51, 1937-1946.
At Wheaton, students “connect” a computer science course with one of two English courses: Anglo-Saxon Literature or Tolkien. Read more about our English-Computer Science connection and check out some of the course materials in the “Computing for Poets” course.
Our Lexos tools enable you to probe your digitized texts without having to program. However, learning to write your own scripts is a powerful addition to your arsenal. Here we share a suite of curated course materials used in an introductory Python programming course where the examples are focused on texts.
NCWIT Engage CS [Search for: LeBlanc Poets ]
Scott Kleinman (California State University, Northridge) is leading our group writing of what we are calling In the Margins, both our tools’ integrated help as well as best-practices comments about the workflow during introductory text mining and experimentation.
The use of computers to manage the storage and retrieval of written texts creates new opportunities for scholars of ancient and other written works. Recent advances in computer software, hypertext, and database methodologies have made it possible to ask novel questions about a poem, a story, a trilogy, or an entire corpus. Check out our web-based workflow to help new users perform computational analyses of digitized texts: Lexos.
Information-rich digital humanities sites