Building toward Critical Data Literacy with Investigations of Income Inequality

To promote understanding of and interest in working with data among diverse student populations, we developed and studied a high school mathematics curriculum module that examines income inequality in the United States. Designed as a multi-week set of applied data investigations, the module supports student analyses of income inequality using U.S. Census Bureau microdata and the online data analysis tool the Common Online Data Analysis Platform (CODAP). Pre- and post-module data show that use of this module was associated with statistically significant growth in students’ understanding of fundamental data concepts and individual interests in statistics and data analysis, with small to moderate effect sizes. Student survey responses and interview data from students and teachers suggest that the topic of income inequality, features within CODAP, the use of person-level data, and opportunities to engage in multivariable thinking helped to support critical data literacy and its foundations among participating students. We describe our definitions of data literacy and critical data literacy and discuss curriculum strategies to develop them.

Authors: Josephine Louie, Jennifer Stiles, Emily Fagan, Beth Chance, and Soma Roy

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