Text Analysis Pedagogy Institute
In partnership with:
- University of Virginia, School of Data Science
- University of Virginia, Library
- University of Arizona, University Libraries
Funding for this 24-month project provided by: The National Endowment for the Humanities
Funding received: September, 2020
The humanities have a valuable research role to play in the era of data science, big data, and machine learning, especially confronting social issues like algorithmic oppression, data privacy, and social media manipulation. The academic, social, and commercial need for humanities data literacy is greater than ever, leading to a growing number of institutes, workshops, books, and online courses. These resources have sprung up to address a knowledge gap between the learning needs of the next generation of humanists and the technical skills of current humanities faculty. In practice, this means emerging humanities text analysts rarely learn the necessary skills through traditional coursework. Over the past year, JSTOR Labs has spoken with more than 200 digital humanities faculty, librarians, and researchers across the United States—from Research 1 to Research 3, Ivy league, small liberal arts colleges, and community colleges—and a handful of digital humanities educators in England, Canada, and Australia. These conversations have confirmed research that argues the greatest challenges for supporting text analysis are not simply access to educational resources, but additionally access to data, community support, and technical infrastructure.
With funding from The National Endowment for the Humanities, JSTOR Labs will partner with The University of Virginia and The University of Arizona to create The Text Analysis Pedagogy (TAP) Institute. Our shared goal will be to help create a national community of practice for teaching and learning text analysis based on open content and infrastructure.
- University of Virginia (Dr. John Unsworth, Dr. Philip Bourne, Dr. Rafael Alvarado)
- University of Arizona (Sarah Shreeves and Megan Senseney)
Our 2022 Instructors:
- Sylvia Fernández Quintanilla (Washington State University)
- Grant Glass (University of North Carolina at Chapel Hill)
- Nathan Kelber (JSTOR Labs)
- William Mattingly (Smithsonian Data Science Lab)
- Rubria Rocha De Luna (Texas A&M)
- Xanda Schofield (Harvey Mudd College)
- Melanie Walsh (University of Washington)
Each institute will host workshops by master teachers on advanced methods and engage participants to create new, open educational resources that combine executable code environments with educational materials designed for humanities learners. The institutes will create:
- Master teacher workshops in advanced text analysis techniques
- New open educational notebooks with executable code in Python and R
- An online directory of educators working in humanities text analysis to facilitate community growth and connection
- An online directory of existing books, lessons, workshops, and syllabuses
- An email list and Slack channel for community support and discovery
- A whitepaper that describes the findings of each institute
Interested in Participating?
Please share this information with those you feel may be interested in attending. Even if you are not able to attend, the institute will create open educational resources to help students, teachers, and researchers alike. To stay up-to-date on the text analysis platform from JSTOR and Portico and the upcoming institute, join our mailing list. More information in the coming weeks!