CDH 507 / HUM 507
Spring 2024
Wed 1:30–4:20
Chancellor 103
Grant Wythoff
office hours by appointment
‡
This graduate course provides a foundation in the history, concepts, methodologies, and tools of digital humanities research. Students learn to critically evaluate and incorporate computational and data-driven methods into their research, and achieve a baseline fluency in accessing, filtering, and analyzing humanities datasets. No prerequisites or preexisting technical skills are required. Students working with texts, images, and artifacts are welcome. Enrollment preference will be given to students pursuing in the Graduate Certificate in Digital Humanities.
Learning Outcomes
In this class, students will:
- Gain fluency in the current landscape of platforms, tools, and techniques for computational and data-driven research in the humanities. In particular, students learn the basics of the command line, and Jupyter (Python) notebooks, and QGIS.
- Locate their home discipline within the wider galaxy of humanistic inquiry. How are quantitative methods and data science impacting their field, as well as the humanities writ large?
- Learn about the rise of so-called “artificial intelligence” in the world today and what interventions humanities researchers offer the way these technologies construe meaning.
- Prepare a research plan for a DH project, either as a conference presentation, a dissertation chapter, a standalone research article, or a curated dataset.
- Read ~70-100pp / week of recent scholarship spanning history, literary studies, art history, and other humanities disciplines engaged in the use of computational methods.
Assignments
Assignments for the course include:
- 40% | Final project.
- 30% | Completion of hands-on exercises with DH tools & methods. Work will be done both in and out of class.
- 30% | Discussion contributions before, during, and after class; attendance.