Building Equitable Education Datasets for Developing Nations: Equity-Minded Data Collection and Disaggregation to Improve Schools, Districts, and Communities

Abstract

Many studies of education engage with large datasets to attempt to solve educational problems. However, no studies have provided a systematic overview of how large datasets could be compiled with an eye toward solving educational problems related to equity, especially as it relates to racial, gender, and socioeconomic equity. This study provides a synthesis of literature and recommendations for how developing nations can learn from peers and collect, disaggregate, and analyze data in ways that promote equity, thus improving schools, school districts, and communities.