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Direct linkKaren Ramlackhan; Yan Wang – Urban Education, 2024
We used the Stanford education data archive (SEDA) data to examine the heterogeneity among urban school districts in the United States. The SEDA 2.1 includes data sets on students' mathematics (Math) and English language arts (ELA) achievement from 2008 to 2014 at the district level. Growth mixture modeling was used to uncover the underlying…
Descriptors: Urban Schools, Academic Achievement, Mathematics Education, English Curriculum
Download full textAlmond, Russell G.; Sinharay, Sandip – ETS Research Report Series, 2012
To answer questions about how students' proficiencies are changing over time, educational researchers are looking for data sources that span many years. Clearly, for answering questions about student growth, a longitudinal study--in which a single sample is followed over many years--is preferable to repeated cross-sectional samples--in which a…
Descriptors: Educational Research, Case Studies, Research Methodology, Literature Reviews
