Sean Reardon: Using Big Data to Measure Educational Opportunity and Inequality

Join us in welcoming an Educational Policy Innovation Collaborative (EPIC) Distinguished Speaker, Sean Reardon.

We test students a great deal in the United States. In grades three through eight alone, U.S. students take roughly 50 million standardized state accountability tests each year. Their scores on these tests, aggregated within geographic school districts and student subgroups, provide useful proxy measures of the sets of educational opportunities available to children in different communities and groups. In this talk, Reardon describes the construction and use of a population-level data set (the Stanford Education Data Archive, or SEDA) based on 300 million tests taken by public school students from 2009-2015. Using these data, Dr. Reardon will describe the patterns and correlates of academic performance and racial/ethnic achievement gaps at an unprecedented level of detail, with a particular focus on the role of socioeconomic context and segregation patterns in shaping opportunity. These data reveal a great deal about patterns of educational opportunity in the United States.

About the speaker

Sean Reardon is the endowed Professor of Poverty and Inequality in Education at Stanford University. He focuses on the causes, patterns, trends, and consequences of social and educational inequality, the effects of educational policy on educational and social inequality, and applied statistical methods for educational research.

Due to limited space, please reserve at EPICedpolicy@msu.edu.