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ENGL 208 A: Data And Narrative

Meeting Time: 
MW 2:30pm - 4:20pm
OUG 141
Kimberlee Gillis-Bridges
Kimberlee Gillis-Bridges

Syllabus Description:

Course Description

English 208 examines the contexts and impacts of various data and the narratives created around them. Students will develop data literacies as they examine how data are communicated through narrative: the stories data tell for good or ill; the stories we tell about data; the harm and histories of various data; and the content data narratives obscure. In addition to learning how to critique data presented as objectively neutral, students will complete projects that critically examine methodologies and technologies of data collection, data representations, as well as the political, cultural, and social uses of data. Moreover, they will learn how to use data strategically and ethically in their own work.

English 208 fulfills the W requirement as well as the data studies course requirement for the Data Science minor.

Learning Objectives

By the end of the course, students will be able to:

  1. Analyze how historical, political, and cultural contexts affect data collection and the creation and understanding of data narratives.
  2. Engage competing approaches to data science methodologies, collection, and narratives.
  3. Assess different kinds of data-based evidence, and interpret and identify patterns in its representation.
  4. Describe how data stories work within various rhetorical contexts.
  5. Integrate data into writing for a variety of purposes and audiences.


Course activities promote active learning, with most class sessions incorporating a mix of mini-lectures, discussion, and group work. The course design—which includes frequent non-graded and graded writing—reflects the importance of writing as a means of learning. My role is to provide the tools and resources you will need to advance your own thinking. I will pose questions, design activities to help you think through these questions, and respond to your ideas. Your role is to do the hard work—the critical thinking, discussion, and writing. You will learn data studies methodologies, analyze stories told with and about data, present your ideas, and constructively respond to your peers’ claims.



Class discussion constitutes one key method for developing your analytical skills. Thus, I expect prompt, regular attendance and active participation in discussions of texts. You should come prepared for each class session, with required reading and online responses completed. During class discussions, students should plan to ask questions, offer analyses, reference relevant reading passages, write to generate ideas, or contribute to and share findings of small-group exchanges. Students should also expect me to call on them, as I want everyone to earn full credit for class participation. Like all skills, speaking in class becomes easier with practice. I do not expect fully polished analyses in class discussion; rather, your contributions represent ideas for further development.

Because students will have multiple, sometimes conflicting, takes on course topics, we will establish norms for maintaining a respectful classroom environment early in the quarter.

Our classroom technology allows both instructor and students to share electronic materials. Therefore, I ask that you bring a laptop to class if possible. Because the presence of student laptops and wireless internet access present the temptation of email and the web, students must follow basic ground rules:

  • Students should switch off and stow their cell phones before class begins.
  • Students may use laptops to take notes, share content generated during small-group exercises, participate in polls, and research questions posed in class discussion; however, they should not check email, electronically chat, update their social networking status or surf the web during class unless asked to do so.

I assess participation daily on a credit/partial credit/no credit basis. Students who participate in good faith and whose comments demonstrate adequate preparation receive full credit. Lack of engagement in class activities, inadequate preparation, and failure to adhere to classroom climate guidelines will substantially lower your participation grade for the course.

Online Reading Responses

Students will use the Canvas class posting board to respond to readings. Each week, I will pose questions about course texts. In a 250- to 300-word response, you may address one of my questions or introduce another point. Feel free to engage your classmates’ ideas as you write. The electronic postings allow us to extend class conversations, raise issues for in-class discussions, and develop ideas for presentations and projects. Your postings receive points on a credit/partial credit/no credit basis, with full points granted to on-time postings that meet the length requirement and demonstrate thoughtful engagement with the questions provided.



Throughout the quarter, groups of 3-4 students will give a 15- to 20-minute presentation that applies concepts from a course reading to analyze a recent data-based narrative. They will also design and lead a discussion activity based on their presentation. The presentation will be graded on focus, argument, complexity, supporting analysis, and delivery/activity leading, with groups receiving 0-12 points in each category. Students will also receive individual points for submitting an assessment of themselves, fellow group members, and the group’s collaboration process.


Students will compose two projects on assigned topics. The first—which will take the form of an essay with integrated visuals—analyzes an existing data-based narrative. The second—which may take essay, website, video, or other multimodal formats—requires students to compose their own data-based narrative as well as assess that narrative’s potential uses and limitations. Projects will be graded on a point scale, with attention to argument, complexity, supporting analysis, strategic use of genre conventions, style and citation.

We will go through a drafting and feedback process for each project, with students giving feedback to and receiving commentary from two peers. We will discuss how to provide effective feedback as well as how to use peer commentary to revise your work. In addition to undergoing peer review, students may share ideas-in-progress and drafts with me during office hours. They may also seek feedback from consultants at the CLUE Writing Center in the Mary Gates Commons and the Odegaard Writing and Research Center in Odegaard Undergraduate Library.

Connecting with the Instructor and Other Students in the Class

Drop-In Hours

You need not have a specific question about the class, course texts, an assignment, or work-in-progress to attend my drop-in hours. I’m available every Monday and Wednesday from 9:30-10:30 a.m. to talk about your interests, experiences at UW, or even the class. Feel free to visit me in person in Padelford A-305 or via Zoom ( If you cannot make my scheduled drop-in hours, please contact me to set up an alternative time.

Community Forum

The Community Forum is an asynchronous space where you can ask general questions about the course, readings, or assignment prompts. Posting questions in the Community Forum helps others with the same question. It also allows students to share answers the instructor might not have.


All course texts are available in electronic format via the UW Libraries or the course Canvas site. We will read excerpts from the following books:

  • Battle-Baptiste, Whitney and Britt Rusert, Britt (Eds.). E. B. Du Bois's Data Portraits: Visualizing Black America. Princeton Architectural Press, 2018.
  • Benjamin, Ruha. Race after Technology: Abolitionist Tools for the New Jim Code. Polity, 2019. Available in ebook form via UW Libraries.
  • Clemmons, Zinzi. What We Lose: A Novel. Penguin Books, 2018.
  • D'Ignazio, Catherine and Lauren F Klein. Data Feminism. MIT Press, 2020. Available in ebook form via UW Libraries.
  • Dykes, Brent. Effective Data Storytelling: How to Drive Change with Data, Narrative, and Visuals. Wiley, 2019. Available in ebook form on multiple platforms via UW Libraries.
  • Egan, Jennifer. A Visit from the Goon Squad. Knopf Doubleday Publishing Group, 2011.
  • Larsen, Reif. The Selected Works of T. S. Spivet: A Novel. Penguin Books, 2016.
  • Noble, Safiya Umoja. Algorithms of Oppression: How Search Engines Reinforce Racism.  New York University Press, 2018. Available in ebook form via UW Libraries.
  • O'Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York: Crown Publishing, 2016. Available in ebook form via UW Libraries.
  • Williams, Sarah. Data Action: Using Data for Public Good. MIT Press, 2020. Available in ebook form via UW Libraries.

Additional Texts

As needed, we will read, listen to, or view recent articles, websites, videos, podcasts, and datasets connected to course topics and contemporary issues. These readings will be available via the course Canvas site.




Since reading responses form the basis of in-class discussion, I will not accept these assignments late, nor will I allow students to reschedule presentations or submit late peer reviews. Projects are due on the dates/times indicated on the course schedule. Late projects will receive a 10-point deduction per day late, including weekends and holidays. I will make exceptions to the lateness policy only in cases of illness or family emergency. You need not document your illness or emergency, but please contact me as soon as possible if you know you cannot meet a deadline.

Technology glitches do not constitute valid excuses for lateness. To avoid computer problems, you should save frequently while working and you should back up work saved to a hard drive on a USB drive or an online file archive (Dropbox, iCloud, Google Drive, your personal file space on Canvas). When submitting files or URLs to Canvas, you are responsible for copying/pasting the correct URL or selecting the correct file. If Canvas breaks down, contact and email your work directly to me.

Academic Integrity

English 208 adheres to the University of Washington’s Student Conduct Code, which prohibits academic misconduct like distributing instructional materials outside class without permission, cheating, and plagiarism: the unacknowledged use of others' words or ideas. All online readings, visual aids, lectures, discussions, and other handouts are for enrolled students only. When drawing upon sources in your reading responses, presentation, and projects, make clear to your audience that you are incorporating others’ work by placing quotation marks around exact words and noting the author’s name whenever you quote, summarize, paraphrase, or reproduce data visualizations. Plagiarism may result in a failing grade for the assignment, a failing grade for the course, or other disciplinary action. Disseminating course materials without permission may result in sanctions, including dismissal. If I see evidence of academic misconduct, I will make a report to the Community Standards & Student Conduct office.


Email and Access to Course Canvas Site

You must have a UW Net ID, a working email account and a way to access the course Canvas site. All handouts, assignment prompts, lecture slides and online readings will be distributed via Canvas, and you will submit class work using the platform's assignment and discussion features. Note that the Student Technology Fee loan program has laptops available for checkout if you need a computer.




Disability accommodations grant students with ongoing or temporary disabilities access to educational opportunities. Disability Resource for Students (DRS) works to ensure access for students with disabilities by designing and implementing accommodations. If you experience educational barriers based on disability, please visit Disability Resources for Students (DRS) online for more information about requesting accommodations. If you have already established accommodations with Disability Resources for Students (DRS), please communicate your approved accommodations to me at your earliest convenience so we can discuss your needs in this course.

Your experience in this class is important to me, and you may have accessibility needs not covered under DRS’s umbrella—for example spotty internet access, an unreliable computer, etc. Please talk with me as soon as possible so we can brainstorm solutions.

Religious Accommodations

Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW’s policy, including more information about how to request an accommodation, is available at Religious Accommodations Policy ( Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form (


Grades in English 208 will be computed by points, with 400 points equaling a 4.0, 300 points a 3.0, and so on. If your total falls between grades, I will round up if you score one to five points below the higher grade and round down if you score one to four points above the lower grade. For example, 274 points equals a 2.7 and 275 points a 2.8. Students who score less than 65 points total will receive a 0 for the course, as the UW grading system does not scale grades lower than 0.7.

Apart from participation and responses, which are graded on a credit/partial credit/no credit basis, points for each assignment will be awarded based on quality of work submitted. I will distribute grading criteria with all assignments. Each component of the course is worth the following number of points:

  • Class participation: 60 points
  • Responses: 100 points
  • Presentation: 60 points
  • Projects: 180 points
Catalog Description: 
Contexts and differential impacts of various data and the narratives created around them. How data are communicated through narrative: the stories data tell for good or ill; the stories we tell about data; the harm and histories of various data; the content data narratives obscure; and their asymmetrical effects on diverse groups. Offered: AWSpS.
GE Requirements: 
Diversity (DIV)
Writing (W)
Last updated: 
May 31, 2022 - 2:36pm