Updated April 17 2020

In Class Participation: 20%

This grade is an evaluation of how much you engaged with both the course and your peers. Forms of participation include:

  • Participating during in-class discussion. This includes sharing ideas from the readings that you found particularly interesting or troubling, as well as posing questions about ideas or concepts you are working through
  • Finding and sharing relevant materials, like recent articles or projects
  • Pair programming (a concept described under Guidelines for Coding) and assisting one another with coding assignments Providing peer review or feedback of each other’s work
  • Visiting during office hours to discuss your projects and subjects of interest

You are able to drop your three lowest participation grades and I will make available your weekly participation grade so that you can evaluate your performance.

Weekly readings and assignments: 15%

Each week you will complete small assignments to help you engage with the readings and programming concepts. For weekly readings, you will be required to submit three questions in advance of class to the instructor via Slack. Please see Guidelines for Reading below for more about the strategy for reading and asking questions. Potential questions to submit from readings include:

  • How did the arguments in each reading overlap? Were the arguments in opposition?
  • What connections did you identify across readings?
  • Was there aspects of the readings that were inspirational or infuriating? If so, which ones?
  • What did you not understand in the readings? What was confusing?
  • What do you want to learn more about?

You will also have weekly programming assignments to complete and share either via Slack or Github. These assignments are intended to reinforce the lessons from our meetings and help you learn to work in pairs or small groups when coding. Please see Guidelines for Coding below for more about policies for programming work.

Both reading responses and coding assignments will be graded as pass/fail, and extensions can be granted for the coding assignments but need to be requested prior to class.

DH Review assignment: 20%

You will select two articles from Current Research in Digital History (https://crdh.rrchnm.org/ ) and write a review comparing them. Drawing from readings in the class, you will situate the articles in broader trends in digital humanities. Your review should answer the following questions: What was the stated goals of the article? Was the article successful in achieving those goals? How would you evaluate their success? How did each article integrate digital methods? Did they use similar methods or differing ones? What sorts of data did each article use? Did the authors define data in the same way? How did the articles utilize visualizations for their arguments? How do the articles relate to earlier trends in DH? Was the article authored by a team? Is the article part of a larger DH project? Ultimately, this review should go beyond summarizing the articles to exploring their scholarly contribution to digital humanities. When selecting which articles to review consider which areas of digital humanities interest you and that you might want to include in your research. The review should be between 2-3 pages single spaced (~1000-1500 words) and be loosely modeled on Reviews in DH format (i.e. focus on not just summarizing, but also contextualizing and critiquing these articles). You will need to get instructor approval of your articles before you begin working on the assignment.

Digital Humanities Project: 45%

The goal of this project is to expose you to how digital humanities research is created and evaluated. Working in groups OR individually you will select a humanities research question and relevant datasets. Example projects include exploring character networks in a set of novels to understand gender disparities, or correlation analysis of place names in historical documents to analyze spatial imaginings. Using your skills in Python and your knowledge of digital humanities, you will experience the lifecycle of a digital humanities project, from planning the project and collecting data to analyzing and communicating your results, and finally reflecting and outlining future directions.

The instructor will provide a list of available datasets and relevant readings that students can use as the basis for their project, but students are also encouraged to also develop their own datasets and research questions if they have a strong interest in a particular topic.

The first stage of the project is worth 10% and is your initial project proposal. If working as a group you will collaboratively agree on a project. Regardless, you will research and create an initial project write-up, answering the following:

  • What are your initial research questions?
  • What scholarship does your research draw upon and further? (This could be digital humanities scholarship, or broader questions in relevant humanities fields)
  • How you will translate your research questions into hypotheses?
  • Which methods and datasets do you plan to use?
  • How do you plan to communicate your results? This write-up should be 2-3 pages and should lay the groundwork for the project, including a timeline to completion and how you plan to divide the work required to make the project.

The second stage is worth 15% 10%, and involves building the first iteration of the project to be presented to the instructor. You will demo the project and explain how much you have completed from the initial write-up. Then through feedback from the instructor and your peers, you will assess how much progress you have made and whether you need to change directions or revise any goals.

Detailed guidelines for first demo For individuals plan to present for 10 minutes (15 minutes max), for groups plan to present for 15 minutes (20 minutes max).

Your presentation should:

  • Introduce your project through summarizing your initial proposal (including your initial research questions, planned datasets, and methods)
  • Demo your initial data collection through exploratory data analysis and give us a brief data biography of your dataset
  • Outline what you plan to do next in the project and whether you need to change course from what you outlined in your initial proposal

Please also be ready to listen to your peers’ presentations and give feedback.

Detailed guidelines for final project The final stage is worth 20% 25%, with the first 12.5% allocated to the public presentation of your project in our final class. The second 12.5% is an individual reflection piece (4-5 pages) on the experience of building the project, the successes and failures of the project, and your vision for the future directions of this project.

To help with the final project, please checkout the final project resources page.

Presentation Guidelines

Presentations should be 15-20 minutes and unlike the initial demo this presentation should present a narrative structured around your research question (rather than you experience doing the research.)

You should begin with an introduction to your question and why it is of interest or significance. Then you should explain the rationale for dataset selection, as well as how you obtained the data. You should include a discussion of what did or did not work, and how you shifted your question based on the data available.

Then you should introduce the methods you decided to use (explain relevant background concepts if you are using more complex methods) and your rationale for selecting them. Finally you should discuss your results. What did you expect to find? Was there anything surprising or was everything expected? What would future research questions explore? How has this changed your understanding of this topic? This section should include at least one visualization, but remember that the best interpretations usually present data through multiple visualizations.

Ideally, you will also bring in some of the topics we’ve discussed over the course of the semester and include some mention of how your project might this be relevant to digital humanities (not necessarily research questions, but maybe in terms of methods or datasets).

You do not need to follow the order of these guidelines in terms of how you structure your presentation. Also you can use slides, jupyter notebooks, or any other documents to present your materials. After your presentation, we will have ten minutes for question and answer, and just like the demo you will complete a final self assessment survey.

Paper/Blog Post Guidelines

For the final piece of the project, you have a choice of either a final reflection paper or a blog post to be hosted on the CDH website.

The final reflection paper will be 4-5 pages double spaced and detail your experience of building the final project. This paper is a chance to critically reflect on what worked in your final project and what did not, as well as what you might do in the future with this project. Ultimately, the reflection paper is intended to be a chance for you to articulate what you learned about data driven research in the humanities. To that end, final reflection papers should reference at least four of the readings from class and detail how your project impacted your understanding of digital humanities. Final reflection papers are due by midnight May 12, 2020.

The blog post format covers some of the same material but is more focused on explaining your final project to a public audience. The blog post should cover some of the similar material from your presentation, mainly your research questions, rationale for your methods, and how you’ve interpreted your results. You should explain how you feel your project relates to discussions we’ve had in the class and reference at least two readings. The blog post will be at least 750 words but no more than 2000 words. Blog posts are also due by midnight May 12, 2020. However, because they are for a public audience, I will help you copy edit the final version and display your visualizations.