The Investigating U.S. Society with Data (USS-DATA) curriculum modules are designed to promote high school students’ statistical thinking and data literacy skills through investigations of social and economic conditions in the U.S. To conduct these investigations, students analyze large-scale U.S. population data using CODAP, an online platform that supports conceptual understanding of statistical ideas and interactive data visualization. Students learn and apply fundamental data practices from the Common Core State Standards for Mathematics and from widely recommended statistics education guidelines as they examine questions of relevance and social importance to themselves, their families, and communities.

With funding from the National Science Foundation (grant #1813956), these modules were developed by an interdisciplinary group of curriculum developers, education researchers, statistics educators, and technology developers who have worked collaboratively and iteratively with high school mathematics and social studies teachers to design and test the modules with hundreds of students over several years. Early-stage research has found that classroom use of the modules in high school mathematics classes is associated with statistically significant growth in students’ understandings of core statistics concepts and interests in data analysis. 

Investigating Income Inequality in the U.S.

In this module, students examine patterns of income inequality among different groups in society over the past century using person-level microdata from the U.S. decennial census and the American Community Survey. Students describe, compare, and make sense of quantitative variables when addressing questions such as: How have incomes for higher- and lower-income individuals changed over time? How much income inequality exists between males and females in the U.S.? Does education explain the male-female wage gap? Designed for high school mathematics classes, the module contains seven lessons, culminates in a final team data investigation, and can be completed in 15 one-hour class periods. 

• Lesson Overviews, Learning Objectives, & Sample Lessons

Investigating Immigration to the U.S.

In this module, students examine patterns of immigration in the U.S. over the past century using person-level microdata from the U.S. decennial census and the American Community Survey. Students describe, compare, and make sense of categorical variables when addressing questions such as: Are there more immigrants in the U.S. today than in previous years? Where have most immigrants been coming from? Are immigrants as likely as the U.S. born to be participating in the labor force? Designed for high school mathematics classes, the module contains seven lessons, culminates in a final team data investigation, and can be completed in 15 one-hour class periods.

• Lesson Overviews, Learning Objectives, & Sample Lessons

Journal Articles and Book Chapters

• Louie, J., Fagan, E., Stiles, J., Roy, S., Chance, B. (2023). Advancing social justice learning through data literacy. Educational Leadership, 80(8), 45-51. https://www.ascd.org/el/articles/advancing-social-justice-learning-through-data-literacy 

• Engel, J., Nicholson, J., Louie, J. (2023). Preparing for a data-rich world: Civic statistics across the curriculum. In Ridgway, J. (Ed.), Statistics for Empowerment and Social Engagement (pp. 445-475). Springer. https://link.springer.com/chapter/10.1007/978-3-031-20748-8_18 

• Louie, J., Stiles, J., Fagan, E., Chance, B., & Roy, S. (2022). Building toward critical data literacy with investigations of income inequality. Educational Technology & Society, 25(4), 142-163. https://drive.google.com/file/d/1JJsKkvtm8Lp1V-olrSssHNfX5aIi2K6Z/view 

• Louie, J., Stiles, J., Fagan, E., Roy, S., & Chance, B. (2021). Data investigations to further social justice inside and outside of STEM. Connected Science Learning, 3(1). https://www.nsta.org/connected-science-learning/connected-science-learning-january-february-2021/data-investigations 

Conference Papers & Posters

• Louie, J. (2022). Critical data literacy: Creating a more just world with data. Commissioned for the Workshop on Foundations of Data Science for Students in Grades K-12, the National Academy of Sciences. https://www.nationalacademies.org/documents/embed/link/LF2255DA3DD1C41C0A42D3BEF0989ACAECE3053A6A9B/file/D16254F310D01BBDA873920E4EFB8151F2D8334181AA?noSaveAs=1  

• Louie, J., Roy, S., Chance, B., Stiles, J., & Fagan, E. (2021). Promoting interest and skills in statistical and multivariable thinking with social justice data investigations. In Proceedings of the International Association for Statistical Education (IASE) 2021 Satellite Conference, Online Conference. https://iase-web.org/documents/papers/sat2021/IASE2021%20Satellite%20133_LOUIE.pdf?1649974212

• Louie, J., Chance, B., Roy, S., Fagan, E., Stiles, J., & Finzer, W. (2021, June). Building statistical thinking with social justice investigations and social science data [Poster presentation]. 2021 DRK-12 PI Meeting, Online Conference. https://cadrek12.org/sites/default/files/Strengthening%20Data%20Literacy%20across%20the%20Curriculum.pdf 

Blog Posts

• Louie, J. (2021, March 2). “Working to Promote Data Literacy and Social Justice.” EDC Innovations Blog. https://www.edc.org/blog/working-promote-data-literacy-and-social-justice

• Louie, J. & Stiles, J. (2022, June 29). “To Understand Society, We Need to Look at Data.” EDC Innovations Blog. https://www.edc.org/blog/understand-society-we-need-look-data