How do data savvy experts make quantitative research on political topics readable to the broader public? We’ll focus on ways to accurately capture and convey complex topics while unpacking misleading, uninformative, and otherwise unsatisfactory graphs and statistics. This course will broadly focus on two primary components of meaningful research engagement with headline political topics: data literacy and honest, concise description. Over the quarter, students will be exposed to different theories of data science and visualization paired with applied examples of the portrayal of data in popular media. Particularly, we will hash out the dos and don’ts of writing about political or potentially controversial topics for broad audiences, as well as how to dispel misinformation with your own analyses. Students will then learn how to translate these skills into data-informed, public scholarship of their own. Using reputable public opinion data or broadly accessible political science datasets, students will engage with data journalism and author their own public-facing pieces that are in conversation with relevant political headlines—mindful of maintaining rigor while speaking to a diverse audience.
An entry level empirical statistics course, such as POLISCI 210 or the statistics department equivalent, are required. Basic familiarity with statistical programming in R is encouraged.
Don't email, just show up!
Mondays 2-4
Thursdays 1 hour before class and 1 hour after
- Applied management of data:
This course will ask students to apply their computational skills to the wrangling, analysis, interpretation, and visualization of different types of data from disparate contexts. The assignment load requires that, by the end of the course, students will have worked with several data sources, computational packages in R, and troubleshot coding problems by themselves or with peers, such that they can engage in similar tasks independently.
- Writing for public audiences:
All writing and visualization tasks in this course will require that students speak about political topics in different tones and registers. The assignments will require that students adapt their interpretation and visualization of political data for different audiences, as well as think about how to reconfigure existing academic literature toward more public facing consumption.
- Critical engagement with concepts in political science:
Students will be exposed to political science concepts that they must not only understand substantively, but also engage with toward the end of meaningful visualization in relation to other concepts and variables. Students will address how to think about measurement, scaling, and utility of different variables in relation to the political science concept that they are trying to model.
- Project management and peer review:
The deliverables of the course will all be subject to peer review and constructive criticism. This will require that students engage thoughtfully in building out their portfolio over time and the design space that they choose. Furthermore, peer review relationship will require that students build rapport with one another to offer substantive comments to classmates regarding their work, building professional skills about how to offer constructive, helpful comments that are within the scope of the writer’s and course’s goals.
Build a Blog—Process (80%)
Over the course of the quarter, students will be required to build a GitHub site or Substack blog—the privacy of which is up to the student, so long as it is available to the class. The build of this site will be phased through the quarter. Students are highly encouraged to read how to make these sites accessible to individuals with different abilities.
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Initial site build and accessibility- 10%
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Visualization Blogs- 15%
Throughout the quarter you will have 3 opportunities to submit a visualization blog of the week. The subject of these blogs will be released by the instructor in the week prior to each blog's due date.
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2 Short Form Blogs with relevant, original data visualizations - 30%
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Final Blog Compilation
a. Edit & Redesign (10%): At the end of the quarter, you will redesign, edit, and proofread all previous blog submissions based on your peer and instructor review, as necessary.
b. Academic Translation (15%): As a final addition, you will also be required to translate a piece of already published political science work into a public-facing piece. This will be specifically interesting if you are able to nest it in historical news headlines—as if it were written when the headlines were relevant.
As a note, the work may seem like a lot to begin with. However, you are welcome and encouraged to use drafts of your visualization blogs in your short form blogs!
Participation (20%)
Attendance in class is mandatory. The participation grade will be dependent on participation in class AND peer-review of other students’ materials. Over the quarter, you will have a class peer that will be your peer-reviewer for all submitted assignments, except for the visualization blogs. The participation grade will reflect your satisfactory completion of peer-review tasks.
Not graded, but highly encouraged to stay up with the needs of the class.
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R
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RStudio
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GitHub Desktop
Course and university policy related to academic integrity, COVID-19 expectations, and accommodations for individuals with disabilities
| Date | Assignment |
|---|---|
| 10/3/2022 | Site Build Due |
| 10/10/2022 | Visualization Blog 1 |
| 10/24/2022 | Short Form Blog 1 |
| 10/31/2022 | Visualization Blog 2 |
| 11/14/2022 | Short Form Blog 2 |
| 11/21/2022 | Visualization Blog 3 |
| 12/9/2022 | Final Blog Compilation |