Course Title: Data and Writing for Social Change
Author: Daniel Libertz, Baruch College, City University of New York
Date Published: 2025
Course Level: Upper-Level Undergraduate
Course Description: This course focuses on critical evaluation of data in application to writing projects that students will produce in class. Students will explore questions such as: What counts as “data”? Who decides? Are data “neutral”? What is the range of possibilities to communicate and write with data? What are important rhetorical considerations at all stages of the lifecycle of data (e.g., collection, cleaning, analysis, interpretation, communication)? What is the “status quo” of data and how does that include and exclude marginalized groups like women, people of color, disabled people, and LGBTQ people? Students will get practice working with data-driven texts produced by others (e.g., academics, journalists) and basic descriptive statistics to consider various rhetorical considerations in creating data-driven arguments and narratives in a variety of genres for a variety of audiences. No expertise in data science or statistics is required or expected. However, students with coursework in those and related fields are welcomed to this course and can apply what they have learned elsewhere in writing projects for this class.
Learning Outcomes:
- Demonstrate an understanding of how data are created, who creates data, and what limitations particular data have in relation to arguments and narratives you can write.
- Ask critical questions of data we encounter, especially in terms of ethical considerations for what data purports to represent and limitations in the arguments and narratives we can make with data in our writing.
- Identify how finding, cleaning, maintaining, sorting, filtering, comparing, and analyzing data have rhetorical consequences in writing.
- Create critically informed and persuasive arguments and stories that are well supported by analyses of data (e.g., considerations of accuracy, accessibility, style, organization, visualization).
Teaching Philosophy: I have always been fascinated by how writers have to reconcile the tension of the abstraction and sometimes alienating quality of datafication/quantification with the unique ability of data-driven writing projects to detail phenomenon at a variety of scales and complexities. I wanted students to get hands-on practice at ALL levels of working with data to see how rhetorical and material consequences are embedded from the creation of categories, to the collection of data, to the analysis of data, to the writing about results from analyses of data, and so on. There are choices, with different motivations and consequences, at all of these levels. As writers and also as readers, we should be aware of this reality and practice how to best function within that reality to harness the power of reading and writing with data to do help others. I also wanted to note that I explain the philosophy behind this course in an article in Composition Forum.
