Syllabus
Course info
- Instructor: Dr. Alice McGrath
- Office Hours: Fridays 1-2:30 or by appointment; Carpenter A5
- Course: T/Th 2:40-4:00 PM, Dalton 20
OL 116 - Bryn Mawr College, Spring 2025
Description
“Digital Humanities” includes a variety of ways that computers can be used to explore, analyze, and publish human histories and cultural objects (literature, art, music, and more), as well as the study of computer technologies through humanistic frameworks. This course will provide a general introduction to digital humanities through a combination of reading, discussion, and hands-on digital making. We will begin with digital publication and digitization (multi-modal scholarship, digital collections, creative coding, immersive/3D models, and more) by discussing examples and building our own small-scale projects. We will ask: how can understanding and situating the digital infrastructures we inhabit every day help us imagine new ones? Then we will turn towards humanities data: how are cultural objects represented digitally, and how can computational analysis methods provide insights? What are the limitations and possibilities of these data-centered approaches? Assignments will include visual essays, simple websites, and data visualization; students will learn to work in command line, Python, and HTML, among other digital skills.
Learning goals
Through this course, you will:
- Gain practical computing skills, including work in the command line, Python, HTML, and git
- Build skill in digital communication, including web design and publishing
- Improve data literacy skills, including data cleaning, data presentation, and digital tools for data analysis
- Gain a better understanding of the ways in which computers model and represent human-created materials
- Become familiar with a range of computational analysis and digital publication methods used for humanistic research
- Develop frameworks for critical digital literacy and critical computing
Materials
- Books:
- Most of the readings for this course are freely available as open-access resources. Others will be available through TriPod or via Moodle. You are expected to bring materials to class in print or digital form.
- Technology:
- For many in-class workshops and many assignments, you will need to use a laptop that you have administrative access to in order to install programs. If you do not have a laptop, they are available for loan at Canaday Library.
Assignments
Your grade will be assessed from a combination of short assignments – demonstrating several genres of digital humanities scholarship – as well as your participation in the class and a final research project or portfolio showing your growth over the semester.
Assignment | Worth | Due | Notes |
---|---|---|---|
Participation | 20% | – | Includes attendance, discussion participation, and weekly short responses |
Project review | 10% | 1/31 | A short analysis and review of a Digital Humanities project |
Website | 10% | 2/14 | A simple static website |
Data story | 15% | 3/28 | A data visualization with context |
Visual essay | 15% | 4/18 | A mini-exhibit featuring primary sources and commentary |
Final project or portfolio | 30% | 5/7 | Option A: a published digital humanities project on a topic or format of your choice. Option B: a portfolio site collecting revised assignments and responses, including a self-assessment. |
Attendance & participation
You will be expected to come prepared to every session and participate actively in class discussion. Each person is allowed one absence, no questions asked, but you are expected to make up any work that you missed. If you need to miss additional classes, please reach out to me as soon as possible ahead of time. Repeated absences may affect your participation grade.
Responses
Weekly reflections on the readings or related activities will be posted to Moodle Forum by Monday 11:59 PM and should be approximately 200-300 words. Each student should submit a minimum of 10 responses throughout the semester. In most cases there will be a specific prompt; otherwise, do your best to show how you have engaged with the readings, ask questions, and share ideas and reflections. I view these as an opportunity to participate in and shape the class discussion, so if you are someone who is less prone to speak in class, you are encouraged to engage more frequently in this space.
Policies
Late work
Responses will not be accepted late because their purpose is to stimulate discussion for Tuesday’s class. For other assignments, each student gets an extension on a single assignment. Let me know when you are taking it. Otherwise, Late work will not be accepted.
Accessibility
Bryn Mawr College is committed to providing equal access to students with a documented disability. Students needing academic accommodations for a disability must first speak with Access Services. Students can email accessservices@brynmawr.edu to request an appointment to begin this confidential process. If eligible for accommodations as per Access Services, students should schedule an appointment with the professor as early in the semester as possible to share their verification form and make appropriate arrangements. Please note that accommodations are not retroactive and require advance notice to implement. More information can be obtained at the Access Services website. (http://www.brynmawr.edu/access-services/)
Any student who has a disability-related need to record this class must first be found eligible to do so by Access Services and must share this eligibility with me, the instructor. Class members need to be aware that this class may be recorded.
Religious holidays
Please contact me if you need accommodations related to a religious holiday.
Generative AI
There will be situations within this course where you will be asked to use AI tools to explore how they can be used. Otherwise, I discourage the use of generative AI tools because of ethical, environmental, and pedagogical reasons. Writing assignments should be your original work, not generated by AI. I do not recommend using AI for research because it produces inaccurate information. Use of AI for coding, data processing, and other forms of automation depends on the context and purpose of the assignment: if learning the skill is central to the assignment, AI coding tools should not be used. Otherwise, you may use them as long as you check their output for accuracy and describe how you used them in your submitted work. If you have questions about a particular use case, please feel free to ask.
Content warning
We live in a world that has been and still is shaped by structural inequalities, oppression, and exclusion. It is my belief that study of the humanities must reckon with these conditions and with their cultural traces responsibly and with care; therefore we will consider difficult material. Please consider that your own emotional and intellectual responses to these questions may not be shared by others; enter them humbly.
Schedule
See full schedule with readings or navigate to the page for each week
- DH Basics
- Week 1: What is Digital Humanities?
- Tuesday, January 21: Defining DH
- Thursday, January 23: Digital humanities projects
- Week 2: Computational Thinking
- Tuesday, January 28: The command line
- Thursday, January 30: Introduction to Python
- Project Review Assignment Due: Friday, January 31
- Week 3: The Internet
- Tuesday, February 4: Hyper Text Markup Language
- Thursday, February 6: Design and Access
- Week 4: DH, Activism, and Community Engagement
- Tuesday, February 11: Digital justice
- Simple Website Assignment due February
1214 - Thursday, February 13: Crowd-sourcing
- Friday, February 14: Douglass Day (1-3 PM in Campus Center)
- Week 5: Data basics
- Tuesday, February 18: Data forms
- Thursday, February 20: Data curation
- Week 1: What is Digital Humanities?
- DH Methods and Modes
- Week 6: Data visualization
- Tuesday February 25: Data stories
- Thursday, February 27: Visualizing data
- Week 7: Text analysis
- Tuesday, March 4: Computational humanities
- Thursday, March 6: Methods of text mining
- Statement of Interest due March 7 For students interested in the final project option A.
- Week 8: Mapping
- Tuesday, March 18: Map forms
- Thursday, March 20: Web mapping
- Week 9: Digital Archives & Exhibits
- Tuesday, March 25: Digital Exhibits
- Thursday, March 27: CollectionBuilder
- Data story due March 28
- Week 10: Linked Open Data
- Tuesday, April 1: Principles of LOD
- Thursday, April 3: Wikidata
- Week 6: Data visualization
- Emerging DH
- Week 11: LLMs and Generative AI
- Tuesday, April 8: LLMs
- Thursday, April 10: Generative AI
- Week 12: Critical Making & Creative Coding
- Tuesday, April 15: Critical making
- Thursday, April 17: Creative coding
- Visual Essay due April 18
- Week 13: 3D Modeling & Creative Coding
- Tuesday, April 22: Creative coding
- Optional: Project bibliography, revised proposal, or draft due Friday, April 25
- Thursday, April 24: 3D models
- Week 11: LLMs and Generative AI
- Wrap-up
- Week 14: Review and presentations
- Tuesday, April 29: Reflections
- Thursday, May 1: Presentations
- Final project or portfolio due Wednesday, May 7
- Week 14: Review and presentations