Course Description
English 208 examines the contexts and impacts of various data and the narratives created around them. Students 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 illuminate and obscure. Students will spend the first half of the quarter learning how to critique data presented as objectively neutral. In doing so, they will complete projects that critically examine definitions of “data” and “data storytelling,” methodologies and technologies of data collection, data visualizations, and the political, cultural, and social contexts data stories exist within and serve. During the second half of the quarter, students will conduct research and craft their own data stories. In doing so, 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:
- Analyze how historical, political, and cultural contexts affect data collection and the creation and understanding of data narratives.
- Apply various approaches to data science methodologies, collection, and analysis.
- Assess different kinds of data-based evidence, and interpret and identify patterns in its representation.
- Describe how data stories work within various rhetorical contexts.
- Integrate data into communication for a variety of purposes and audiences.
Methodology
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.
Requirements
Participation
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:
- Speak to the whole class or small groups of peers, asking questions, offering analyses, referencing relevant reading passages, and generating ideas with others.
- Take and/or add to group notes during group activities.
- Respond to polls during mini-lectures.
- Complete in-class writing on assigned questions.
- Share out ideas from in-class writing, small-group discussions, and lab activities.
- Give feedback on peers’ drafts and ideas-in-progress.
Along with contributing to class conversations, students can participate by discussing course texts, ideas-in-progress, or questions with Kimberlee during drop-in hours and answering peers’ questions on the Community Forum.
Like all skills, speaking in class becomes easier with practice. Students should also expect me to call on them, as I want everyone to earn full credit for class participation. 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.
If you must occasionally miss class due to illness, I will provide alternative ways for you to contribute. I may ask you to keep a reading journal, comment on peers’ short assignments, engage in online discussion with others who are ill, or share textual annotations with peers. If I must miss class due to illness or if the university cancels in-person classes, I will email students as soon as possible and move planned activities online.
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 unless otherwise directed.
- Students may use laptops to take notes, participate in polls, share content generated during small-group exercises, access course texts or short assignments, and research questions posed in class discussion
- Students should not check email, electronically chat, update social media, or access 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.
Short Assignments
Students will use the Canvas class posting board to respond to readings or share project work-in-progress. Each week, I will pose questions about course texts or prompts for project development. 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 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.
Projects
Students will compose three projects on assigned topics. The first—which will take the form of an essay with integrated visuals—analyzes an existing data story. The second—which will take the form of a recorded lightening talk—outlines potential stories one could tell with a dataset introduced in class. The third—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 data 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 Others
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 Tuesday and Thursday from 10:30-11:30 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.
Texts
All course texts are available in electronic format via the UW Libraries or the course Canvas site. We will read the following articles and excerpts from the following books:
- Bender, Emily M. and Alex Koller. “Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data.”Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, July 2020. Available as video and PDF at https://aclanthology.org/2020.acl-main.463/.
- Buolamwini, Joy. Unmasking AI: My Mission to Protect What Is Human in a World of Machines. Random House, 2023. 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.
- Pangrazio, Luci and Neil Selwyn. Critical Data Literacies: Rethinking Data and Everyday Life. MIT Press, 2023. 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.
Policies
Lateness
Since short assignments form the basis of in-class discussion, I will not accept these assignments late, nor will I allow students to 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. Failure to submit required project drafts/proposals and participate in the class proposal workshops will result in a 10-point deduction from the final grade, as the ability to consider and revise from feedback is an essential component of the W credit.
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.
Note that 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 help@uw.edu 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.
The course also prohibits using AI to compose assignments. This prohibition applies to online generative AI tools like ChatGPT as well as AI embedded in word-processing, translation, presentation, and grammar/style apps.
All online readings, visual aids, lectures, discussions, and other handouts are for enrolled students only, as are materials produced by other students. 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.
Submitting work authored by another person or AI, failure to credit sources, and sharing materials outside class may result in a failing grade for the assignment, a failing grade for the course, or other disciplinary action. 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.
Accommodations
Access
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 online for more information about requesting accommodations. The DRS office in Mary Gates 011 is open Monday through Friday from 8:30 a.m.-5:00 p.m. Staff can work with you in person, by phone, TTY, video chat, or email (uwdrs@uw.edu).
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 web access, an unreliable computer, etc. Please talk with me as soon as possible so we can brainstorm solutions.
Religious Accommodations
In accordance with state law, UW provides reasonable accommodations for 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 (https://registrar.washington.edu/staffandfaculty/religious-accommodations-policy/). Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form (https://registrar.washington.edu/students/religious-accommodations-request/).
Grading
Assessment System
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.
Short assignments receive credit for meeting due date and minimum length requirements and thoughtfully engaging with instructor prompts. Students who regularly participate as outlined in “Class Participation” will receive full participation points. All other assignments are evaluated based on quality of work submitted. Assessment comes in the form of grades and instructor feedback, either free-form or within a rubric. If you do not understand course readings, instructional materials, or assignment prompts, ask questions in the Community Forum, class sessions, or drop-in hours.
Total Points for the Course
Each component of the course is worth the following number of points. Please note that Canvas does not integrate well with my point schema. Canvas automatically converts points into percentages, a conversion that can make your grade seem lower than it actually is. For example, 10/20 points represents the C range under my system and the F range (50%) under a percentage system. For this reason, I include point range information on each assignment. In short, keep track of your total points and ignore Canvas's percentage conversion.
Grade Component |
Possible Points |
Class Participation |
60 points |
Short Assignments |
100 points |
Project 1 |
80 points |
Project 2 |
60 points |
Project 3 |
100 points |
TOTAL |
400 points |