Review and Journal 2 (10-15 min)
Finding data, contextualizing data, cleaning it, exploring it.
Don’t stop too soon! Something “obvious” or “useless” is an instinct you should not entertain too quickly!
For “obvious,” this does not mean it is not an important thing to write about.
1. Redundancy is GOOD. People are bombarded with information and need to hear things a lot, and more importantly, need to hear it in DIFFERENT ways. E.g., climate change is happening people know that, but they need to hear about it in creative ways to get them interested.
2. Lots of findings from analyzing data might be useless ultimately, but it takes a while to know that for sure. There can always be an unusual aspect or something that confirms something else once you contextualize and think more about it. Share it with others. Sit with it. Think about it. There could be something there, but you might not know that if you rush too quickly past it.
Because getting another perspective on this stuff is important, I want you to take a moment to share with a partner. What did you find was cool? Did you struggle with anything? Any way the other person can provide another perspective to see if it is helpful on either or both of the “cool” and “struggle” parts?
Finally, on CourseWeb, I uploaded one example Journal 2 that I thought did a good job of thinking about different ways to explore their data. Lots of people did a good job, but just wanted to highlight one as an example that might be helpful to you all.
Bring questions about this process to your meeting with me next week.
Making Data Interesting (20-30 min)
As discussed already, we are interested in the *intentional use of symbols* in regard to our use of data and in regard to our goals as writers, the audience(s) we are targeting, and the constraints we are under (e.g., attention span, medium).
For homework, you chose one of three pieces and I asked you to come ready to talk about what intrigued you most as a reader, why, and how moments of quantification were accessible to you in the piece you chose.
In groups based on who selected what, talk about that. In addition, talk about the following:
- Outline the organization of the piece. How does it start? If you could break it up into parts, what would you name each part based on what it “does”?
- How does the language interact with the visuals?
- How is it designed? Is there a good amount of empty space between paragraphs or sections or images? How long are the paragraphs? How is color utilized?
- Is anything complicated? Did you struggle reading any portions? Which portions? Why?
- How did the writer try to make things more accessible for readers at the level of language? Did they use examples? Did they repeat things? Did they define things?
- Did they talk at all about the dataset they drew from (e.g., how it was assembled, definitions of categories)? How about how they analyzed what they analyzed?
- Finally, what about “evaluation.” Did the writer tell you what they thought about what they found or do you think they let the numbers “speak for themselves”? Use evidence from the text to support your position here.
Getting Started with Writing (25 min)
For last class, you read chapter 1 of the Miller book and for today you read chapter 13 from the same book. I know there were probably some concepts from chapter 13 that you didn’t totally get if you haven’t taken a statistics course before (mostly in the first half of the chapter), but much of what was discussed was relevant for all levels of sophistication for different types of analyses of data.
Miller talks about three tools you have as writer for data-driven arguments and narratives:
- Prose
- Tables
- Charts
Different tools do different things. What do you think are the strengths and weakness of each of these tools?
Questions to ask as you start writing:
- How do numbers fit into the story you are telling? How do they answer questions you and/or your audience has?
- Are you telling your audience why you are including numeric information and what it means to you based on your expertise and familiarity with the data? (e.g., something is large or small, typical or unusual, trending up or down, frequent or infrequent). Many times this means making comparisons.
- Have you assessed the interests, abilities, and objectives of your audience? How do you write to accommodate those three elements?
For public audiences, what did you gather from chapter 13 that is especially important?
What genres of writing can you do besides the data journalism pieces? What are their purposes? Their audiences? Who would you represent?
Miller mentions some, but you know others. What else could you do?
Assignments Coming Up (5 min)
-Proposals are due Monday, see schedule.
-Learning Narrative 1 is due next Thursday, see schedule.
-First draft of public writing project will be due on 9/19.
-Keep looking at schedule. I’m going to rearrange some things in late September for homework assignments and lessons.