UC Santa Cruz

This dissertation documented how undergraduate students made sense of data in news media. The participants were 30 undergraduate students enrolled in a course called “Numbers and Social Justice.” The study used argument analysis (Toulmin, 2003) and ethnographic methodology to examine students’ written work in a naturalistic setting. Course lessons and assignments used open-ended tasks focused on socio- political issues using real data from newspapers, media outlets, or social media (Engledowl & Weiland, 2021; Weiland, 2019). Recordings of class meetings (on zoom) and students’ written work were used to explore the following questions: 1) How did students respond in writing to a news article with statistical claims, data, and visual representations of data? 2) What arguments did students write? When students made arguments, what types of arguments did they make? 3) What statistical literacy practices did students use? 3a) Did these change over time and with the opportunity to revise for four focal students? Analysis of students’ essays provided evidence that asset-based instruction centered on statistical practices can support students from non- STEM majors in learning to critically analyze data-based claims. Both the course design and analysis used an asset perspective of students, a perspective that is important for documenting the strengths of learners from non-dominant communities. Analysis documented students from non-STEM majors using data in arguments, participating in statistical literacy practices, and generating and refining their written arguments about data in a news article. The study shows that students who previously felt marginalized from mathematics learned to use statistical practices through instruction that used social justice topics, focused on goals, and provided opportunities to write and revise. Analysis uncovered the need for students to notice goals, highlighted how goals are central for revising arguments, and organized lists of statistics skills into clusters based on inferred goals for students' statistical literacy practices. The study has implications for supporting students in learning to construct stronger arguments about data. In particular, the study shows that writing and revising can provide opportunities for students to slow down, help teachers to notice students’ strengths and offer feedback focused on goals, and may support students in improving their arguments.