Words as Data: Integrating Data Visualizations and English Language Arts for Classrooms With Multilingual Students
This paper presents findings from a design-based research project that integrates quantitative text analytics data visualizations into middle school English Language Arts (ELA) classrooms, with particular attention to multilingual learners. In collaboration with a public school district, we co-designed data visualizations (e.g., word clouds, word frequency graphs) and instructional routines to support literary engagement and text comprehension using quantitative features of text. Drawing on survey data and classroom video excerpts, we examined how students engaged with these materials and how their perceptions of reading and data work changed. Participating teachers aided in visualization and routine design and implemented visualization use at least three times in their classroom. A control group of teachers proceeded with existing curriculum and activities. Compared to a control group, students who participated in these activities—especially those still developing English proficiency—showed more positive shifts in attitudes toward reading and working with data. These findings suggest that lightweight data integrations in ELA can support students' interpretive practices that are emphasized in ELA classrooms while also promoting data literacy, particularly for linguistically diverse populations.
Authors
- Elizabeth Finlayson Harris (ORCID: https://orcid.org/0000-0001-7099-1450)
- Ruishi Chen
- Victor R. Lee (ORCID: https://orcid.org/0000-0001-6434-7589)
- Sarah Levine
Institutions
- Stanford University (US)
Publication Details
- Journal
- Journal of Statistics and Data Science Education
- Published
- 2026-05-08
- DOI
- https://doi.org/10.1080/26939169.2026.2670354
- Primary Topic
- Educational Assessment and Improvement
- Type
- article
- Field-Weighted Citation Impact
- 0.00