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Harris, Douglas N.; Larsen, Matthew F. – Educational Evaluation and Policy Analysis, 2023
Prior research suggests that families prefer schools with higher test scores, shorter distances from home, and certain student demographics. We build on this using data from New Orleans, a context well suited to identification of parent preferences because of its deferred acceptance algorithm and extensive, standardized, and broadly accessible…
Descriptors: School Choice, Preferences, Data, Evidence
Conaway, Carrie; Keesler, Venessa; Schwartz, Nathaniel – Educational Evaluation and Policy Analysis, 2015
State longitudinal data systems (SLDSs) have created more opportunities than ever before for rigorous research to influence education policy decisions. As state practitioners who play central roles in building and using our states' longitudinal data systems, we are excited about their promise for supporting policymaking and research. Yet, we also…
Descriptors: State Departments of Education, Longitudinal Studies, Data, Educational Research
Papay, John P.; Murnane, Richard J.; Willett, John B. – Educational Evaluation and Policy Analysis, 2015
We report results from our long-standing research partnership with the Massachusetts Department of Elementary and Secondary Education. We make two primary contributions. First, we illustrate the wide range of informative analyses that can be conducted using a state longitudinal data system and the advantages of examining evidence from multiple…
Descriptors: Longitudinal Studies, Data, Elementary Secondary Education, Outcomes of Education
Jacob, Robin T.; Goddard, Roger D.; Kim, Eun Sook – Educational Evaluation and Policy Analysis, 2014
It is often difficult and costly to obtain individual-level student achievement data, yet, researchers are frequently reluctant to use school-level achievement data that are widely available from state websites. We argue that public-use aggregate school-level achievement data are, in fact, sufficient to address a wide range of evaluation questions…
Descriptors: Academic Achievement, Data, Information Utilization, Educational Assessment
Dynarski, Susan M.; Hemelt, Steven W.; Hyman, Joshua M. – Educational Evaluation and Policy Analysis, 2015
This article explores the promises and pitfalls of using National Student Clearinghouse (NSC) data to measure a variety of postsecondary outcomes. We first describe the history of the NSC, the basic structure of its data, and recent research interest in using NSC data. Second, using information from the Integrated Postsecondary Education Data…
Descriptors: Clearinghouses, Data, Outcomes of Education, Outcome Measures
Carlson, Deven; Borman, Geoffrey D.; Robinson, Michelle – Educational Evaluation and Policy Analysis, 2011
Analyzing mathematics and reading achievement outcomes from a district-level random assignment study fielded in over 500 schools within 59 school districts and seven states, the authors estimate the 1-year impacts of a data-driven reform initiative implemented by the Johns Hopkins Center for Data-Driven Reform in Education (CDDRE). CDDRE…
Descriptors: Reading Achievement, Mathematics Achievement, Educational Change, Data
Ronfeldt, Matthew – Educational Evaluation and Policy Analysis, 2012
This study is motivated by an ongoing debate about the kinds of schools that make for the best field placements during pre-service preparation. On the one hand, easier-to-staff schools may support teacher learning because they are typically better-functioning institutions that offer desirable teaching conditions. On the other hand, such field…
Descriptors: Preservice Teacher Education, Preservice Teachers, Student Teachers, Field Experience Programs

Drew, David E. – Educational Evaluation and Policy Analysis, 1983
This paper presents a new technique in which covariates are controlled and evaluation data still are presented graphically in a manner that makes sense to policy makers. An illustration is provided using data drawn from an evaluation by the author of a major National Science Foundation (NSF) university funding program. (Author)
Descriptors: Control Groups, Data, Evaluation, Experimental Groups