Schedule

Jump to:

Week 1 | Week 2 | Week 3 | Week 4 | Week 5 | Week 6 | Week 7 | Week 8 | Week 9 | Week 10 | Week 11 | Week 12

This class will meet on Zoom during its normally scheduled time: TR 4:30-6:00pm.

Week 1 - How the Web Works#

Tuesday, August 25, 2020#

  • Getting to know you survey
  • Read What is Humanities Data by class time.
  • Class agenda:
    • introductions + icebreaker: earliest memory of the internet? (4:30-4:45)
    • course overview (4:45-5:05)
    • quick break (5:05-5:10)
    • breakout rooms: course charter (5:10-5:30)
    • review charter together (5:30-5:45)
    • go over activities for Thursday (5:45-6pm)

For Thursday

Thursday, August 27, 2020#

  • How the Web Works!
  • Class agenda:
    • icebreaker: what do you wish you'd known about W&L as a first year? (4:30-4:40)
    • activity 1.1 sharing + discussion (4:40-4:50)
    • activities 1.2 + 1.3 walk through (4:50-5:00)
    • activities 1.2 + 1.3 solo work time + break (5:00-5:15)
    • activities 1.4-1.6 walk through (5:15-5:30)
    • activities 1.4-1.6 work time (5:30-6:00)

Activity log week 1#

Due Monday 8/31 at 9am Wow because of date typo, you have until Tuesday, 9/1 at 9am to submit.

  1. Complete Activities 1.2, 1.3, 1.4. In Canvas, submit the URL webpage that you have coded and uploaded to your domain.
  2. Complete Activities 1.5-1.6. In Canvas, submit the URL to your Wordpress site. There should be evidence that you have customized your Wordpress beyond the basic settings.
  3. Blog post #1. Respond to the following prompt in a 300-500 word blog post on your Wordpress. In Canvas, submit the URL the blog post.
    • Prompt: What brought you to this class? What is your current relationship with technology? Where do you see data in your coursework? Where do you see data in your daily life? What humanities subjects are particularly interesting to you? What are your own goals for this course? What do you want to accomplish/learn/achieve?

Week 2 - Your Computer#

Tuesday, September 1, 2020#

  • Read Your Computer by class time.
  • Class agenda:
    • icebreaker: It's September today. What will you miss the most about summer?
    • breakout groups: review websites in small groups (4:45-5:00)
      • First, share with your partner one realization you had while learning HTML/CSS. It can be technical like "don't forget that slash" or conceptual "I realized I need to read directions more closely."
      • Second, visit each other's hand-coded website (not Wordpress). Share the link in chat. Right click/Ctrl + Click to view page source.
      • Proof your partner's code. Check their syntax. Did they miss any slashes? Is everything in the right place?
      • Work together to add the following to each of your websites:
        • an iframe tag which will embed another website onto your own.
        • two div tags with different background colors (hint, you'll need to use a class or id)
      • Be sure to upload your changes to your website.
    • break (5:00-5:05)
    • start Activity 2.1 together (5:05-5:45)
    • talk about Week 2 blog post

For Thursday:

  • Finish Activity 2.1 and 2.2 by class time.

Thursday, September 3, 2020#

  • Class agenda:
    • icebreaker: what's your favorite comfort tv show? (4:30-4:40)
    • Introduce Final Project (4:40-5:00)
    • Start Activity 2.3 together in breakout rooms (5:00-5:45)
    • Questions??? (5:45-6:00)

Activity log week 2#

Due Monday 9/7 at 9am

  1. Complete Activity 2.3. In Canvas, submit a document with your answers. It is more important that you show your process, thinking, and attempts than it is that you get everything right.
  2. Blog post #2: Respond to the following prompt in a 500 word blog post on your Wordpress. In Canvas, submit the URL the blog post. Prompt:
    • To help us conceptualize humanities data projects, let's look at a few more projects and the accompanying reviews. Scholarly articles and books are typically reviewed by other experts in the field. There are established procedures and venues for this kind of work, however DH projects do not always fit into those procedures. Reviews in DH is a new publication that "bridges the gap" by providing reviews of projects. For this blog post, you will explore and write about a project before reading the accompanying review, then read the review and see how your analysis lines up.
    • First, take a look at the Review Content.
    • Next, select a project to review. The projects on this list have been selected to fit with the content of this course. Remember, don't read the review until you've written about the project yourself!
    • Write 200-300 on the project, using the Reviews in DH guidelines. Remember, you are not an expert yet, so you may not be able to address all aspects of the project.
    • Now read the accompanying review. What did you learn? How did it compare to your review? Write another 200-300 words on the differences in your reviews and the new concepts or approaches you learned. This blog is about process and learning! You are not expected to know everything already! I want to see how you are engaging with new material.

Week 3 - Data#

Tuesday, September 8, 2020#

  • Read the Data chapter by class time.
  • Class agenda:
    • icebreaker: favorite dog breed (4:30-4:45)
    • Activity 3.1 (4:45-5:10)
    • Activity 3.2 (5:10-5:40)
    • Activity 3.3 (5:40-6:00)

For Thursday:

Thursday, September 10, 2020#

  • Class agenda:
    • icebreaker: what is the least interesting fact about yourself? (4:30-4:40)
    • Project Q&A (4:40-4:50)
    • Activity 3.4 (4:50-6:00)

Activity log week 3#

Due Monday 9/14 at 9am

  1. Submit your answers from Activities 3.3 via a document in Canvas.
  2. Blog post #3: Respond to the following prompt in 300-500 words. Time to start thinking about your project! You will conduct this project on your own, though we'll have plenty of opportunities for peer review and feedback. You will choose your topic, so it's time to start brainstorming. What types of humanities-based topics do you find compelling? What subjects are you interested in school and out of school? What might make a good data-driven topic? Maybe you've always wanted to see a map from a particular historical event, or analyze the word choice of a favorite author.

Week 4 - Visualization#

Tuesday, September 15, 2020#

For Thursday

Thursday, September 17, 2020#

  • Class agenda:
    • icebreaker: is there a scary thing from your childhood that still affects your behavior today? (4:30-4:40pm)
    • Discuss readings (4:40-5:00pm)
    • Activity 4.3 (5:00-5:45pm)
    • Regroup (5:45-6pm)

Activity log week 4#

Due Monday 9/21 at 9am

  1. Turn in the results of Activity 4.1 on Canvas.
  2. Write 100-200 words on the visualization you found, addressing the questions in Activity 4.2. Turn this in as a document on Canvas.
  3. Blog post #4: For your blog post this week, go through the same process in Activity 4.3 with the Cemetery data set. You may have to clean up fields in Open Refine or Excel to get the results you're looking for. Post several visualizations, along with a 300-400 word blog post on your results. What is your goal with these visualizations? How do they help you understand the data? How did you put these graphs together? Did you have to clean the data or look up how to create the graph? What did you struggle with? Are you happy with the results? What might you want to do with more time/skills? What have you learned about data visualization?

Week 5 - Network Analysis#

Tuesday, September 22, 2020#

  • Read Network by class time.
  • Read Demystifying Networks
  • Class agenda:
    • icebreaker: favorite chore (4:30-4:40)
    • recap week 4 + intro week 5 (4:40-5:00)
    • Activity 5.1 in breakout rooms (5:00-5:30)
    • Share Activity 5.1 (5:30pm)
    • Talk about homework for this week

For Thursday

Prepare for Activity 5.2. You will be asked to share in class on the project you choose!

Thursday, September 24, 2020#

Activity log week 5#

Due Monday 9/28 at 9am

  1. Spend some more time with the data and networks of Activity 5.4. Upload one network visualization to your website with 150-300 words on what worked and what didn't. What is this network telling you? What is it obscuring? What else do you need to know about the people in this network?
  2. Blog post #5: Time to start your research! Prompt:
    • Review the Research section of the Process chapter.
    • Set a timer for 25 minutes and do some gathering of potential sources and contextual material. Remember your ideas from week 3? This is your chance to explore further. Keep a log of what you find.
    • Take a break, or come back another day and set your timer again. This time your goal is to refine your list into useful sources. You should have at least 2 scholarly sources and at least 2 other sources.
    • Your blog post should include 100+ words on the experience of doing this work. What worked for you? What didn't? What did you discover about the research process?
    • List your 5 sources with 2-sentence annotations. In the first sentence, summarize the source. In the second sentence, say something about why this source is useful for your project.

Week 6 - Spatial Analysis#

Tuesday, September 29, 2020#

Thursday, October 1, 2020#

Activity log week 6#

Due Monday 10/5 at 9am

  1. To complete Activity 6.3, select a second mapping platform to explore (not the one you looked at in class). In a 300-500 words, answer the questions from Activity 6.3, then provide additional commentary on the differences between this platform and the one you looked at in class. Consider how to use the platform and what can be created with it. Use the Coeducation Report data set to create a map, then embed it into your post.

  2. Blog post: Now that we've had more practice reviewing projects, it's time to write your own from scratch! Using the Reviews in DH Review Content criteria, write a 500 word review of one of the following spatial projects:

Week 7 - Text Analysis#

Tuesday, October 6, 2020#

  • Read Text Analysis by class time.
  • Print out this activity packet before class!
  • Class agenda:
    • icebreaker: favorite hike or outdoor location in Rockbridge county?
    • 4 Ways to Read activity (4:45-6)

Thursday, October 8, 2020#

Activity log week 7#

Due Monday 10/12 at 9am

  1. Activity 7.3
  2. Draft your project proposal in preparation for next week's individual consults. This will be your week 7 blog post. It is okay if it is full of questions! If you feel yourself getting stressed out while writing this proposal, please take a break and feeling out the project feelings form! It can be anonymous if you want and will help me prep for our meeting.

Week 8 - Project Planning#

We'll schedule individual meetings this week to discuss your project. Sign up for a time on Box.

I recommend reading all of the Process section if you haven't already!

Due Monday 10/19 at 9am

  1. Your final project proposal is due.
  2. No blog post!

Week 9 - Data Modeling#

Tuesday, October 20, 2020#

  • Class agenda
    • icebreaker: favorite scary movie? (4:30-4:40)
    • Project check-in (4:40-4:50)
      • Data modeling (4:50-5:05)
      • Data plan (5:05-5:20)
      • Data license (5:20-5:30)
    • Wordpress time! (5:30-5:45)

Thursday, October 22, 2020#

  • Open office hours: drop in to ask questions, get feedback, or hang out. (4:30-5:30pm)
  • Continue to use the project feelings form as a place to dump feelings you have about your project! Responses can be anonymous.

Due Monday 10/28 at 9am

  1. The data documentation assignment should be posted to your course website with the link turned in on Canvas.
  2. Blog post week #9: In 250-300 words, let's have a project update! Address the following questions: what did you get done this week? How did it go? What could have gone better? What lessons did you learn this week? What did you learn that will be useful outside this class? What are your goals for next week?

Week 10 - Data Analysis + Visualization#

Tuesday, October 27, 2020#

  • Open office hours: drop in to ask questions, get feedback, or hang out. (4:30-5:30pm)

For Thursday:

  • Prepare 1-2 draft visualizations for peer review! Post them to your website so your classmate can view them.

Thursday, October 29, 2020#

  • Class agenda:
    • icebreaker
    • visualization peer review

Due Monday 11/2 at 9am

  1. Drafts of your data visualizations are due. Post to your website and turn in the link on Canvas. You might find that after conducting analysis and writing about your results that you need to modify your visualizations. That's fine! Final data visualizations will be due 11/9.
  2. Blog post week #10: In 250-300 words, let's have a project update! Address the following questions: what did you get done this week? How did it go? What could have gone better? What lessons did you learn this week? What did you learn that will be useful outside this class? What are your goals for next week?

Week 11 - Results + Interpretation#

Tuesday, November 3, 2020#

  • VOTE
  • Open office hours

Thursday, November 5, 2020#

  • Open office hours

Due Monday 11/9 at 9am

  1. Your project! The results, final visualizations, and updated data are all due.
  2. Blog post week #11: In preparation to present your project in class, draft a 5 minute talk. You have an option when turning this in! It can be a blog post or an audio or video file that you turn in via Canvas. It can be hard to say everything you want to say in 5 minutes! Try to address the following:
    • What is this project about?
    • Why did you select this topic?
    • Where is the data from? What challenges did you face putting it together?
    • What did you learn about your topic? How did the analysis methods help?
    • What would you do differently OR what are the future directions of this project?

Week 12 - Wrapping up + Presentation#

Tuesday, November 10, 2020#

  • Class agenda: 5 minute project presentations

Thursday, November 12, 2020#

  • Class agenda: 5 minute project presentations

Due Friday 11/13 at 11:59pm

  1. Course reflection is due. Upload to Canvas.
  2. Blog post #12: In 200-300 words, reflect on the presentations of your classmates. What was impressive? What was unexpected? What was inspiring? As you think about all the projects together, what can you say about data in the humanities?

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