Collaborative Research: Leveraging Matched Administrative Datasets to Improve Educational Practice and Long Run Life Outcomes: Toward Building a National Interdisciplinary Network

Northwestern University, Evanston IL

Investigators

Abstract

This proposal intends to develop a national community of researchers that utilizes large scale, longitudinal educational databases that are linked across the spectrum of early childhood to college, workplace and other social sets of data. The research collaborative includes an initial group of scholars in education research, education policy, anthropology, economics, psychology and social sciences from Northwestern and Duke University. These researchers are actively recruiting researchers and educational stakeholders from across the country, who are working with different educational and other data sets to improve capacity to link data together in the expanded data repositories that have been funded by the federal government. The researchers are identifying best practices in the use of data and develop prototypes of their use. Starting from the Florida and North Carolina longitudinal data sets, the researchers are developing prototypes of how these data can be combined to answer pressing educational and social science questions that have heretofore been unable to be addressed. These prototypes are being developed collaboratively across the multiple institutions who are participating in the national community, with Northwestern and Duke serving as the conceptual hubs of the project. The prototypes inform the two national level meetings at which scholars and practitioners to share findings and stimulate the development of such research in other states. The expansion of large scale longitudinal data in education and social sciences has resulted in a demand for new ways to link together data that has typically remained in silos across various state agencies. By developing prototypes of how these data sets should be linked, this research and development is expanding the nature of the questions that the data can inform. These questions include important policy and practice concerns that have been problematic in science, technology, engineering and mathematics education.