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50 Years of ERIC
50 Years of ERIC
The Education Resources Information Center (ERIC) is celebrating its 50th Birthday! First opened on May 15th, 1964 ERIC continues the long tradition of ongoing innovation and enhancement.

Learn more about the history of ERIC here. PDF icon

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Koon, Sharon; Petscher, Yaacov – Regional Educational Laboratory Southeast, 2015
The purpose of this report was to explicate the use of logistic regression and classification and regression tree (CART) analysis in the development of early warning systems. It was motivated by state education leaders' interest in maintaining high classification accuracy while simultaneously improving practitioner understanding of the rules…
Descriptors: Classification, Regression (Statistics), Models, At Risk Students
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Koon, Sharon; Petscher, Yaacov; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
This study examines whether the classification and regression tree (CART) model improves the early identification of students at risk for reading comprehension difficulties compared with the more difficult to interpret logistic regression model. CART is a type of predictive modeling that relies on nonparametric techniques. It presents results in…
Descriptors: At Risk Students, Reading Difficulties, Identification, Reading Comprehension
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Folsom, Jessica Sidler; Osborne-Lampkin, La'Tara; Herrington, Carolyn D. – Regional Educational Laboratory Southeast, 2014
This document is a companion guide to "A Descriptive Analysis of the Principal Workforce in Florida Schools" (Folsom, Osborne-Lampkin, & Herrington, in press). It describes the methods used to extract information from the Florida Department of Education database in order to conduct a descriptive analysis of the demographic…
Descriptors: Data, Principals, Demography, Administrator Characteristics
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Petscher, Yaacov; Kershaw, Sarah; Koon, Sharon; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
Districts and schools use progress monitoring to assess student progress, to identify students who fail to respond to intervention, and to further adapt instruction to student needs. Researchers and practitioners often use progress monitoring data to estimate student achievement growth (slope) and evaluate changes in performance over time for…
Descriptors: Reading Comprehension, Reading Achievement, Elementary School Students, Secondary School Students
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Petscher, Yaacov; Kershaw, Sarah; Koon, Sharon; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
Districts and schools use progress monitoring to assess student progress, to identify students who fail to respond to intervention, and to further adapt instruction to student needs. Researchers and practitioners often use progress monitoring data to estimate student achievement growth (slope) and evaluate changes in performance over time for…
Descriptors: Response to Intervention, Achievement Gains, High Stakes Tests, Prediction
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Regional Educational Laboratory Southeast, 2012
What do we know about the impact and implementation of Career Academies? This paper provides answers to this question. Career Academies have been around for over 30 years. Their original design stressed facilitating the school-to-work transition. In the early 1990's the focus began to shift to preparing participating students for both college and…
Descriptors: Intervention, Career Academies, Career Development, Education Work Relationship
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Lewis, Karla; McColskey, Wendy; Anderson, Kim; Bowling, Treana; Dufford-Melendez, Kathleen; Wynn, Lucy – Regional Educational Laboratory Southeast, 2007
When selecting reading across the curriculum interventions, educators should consider the extent of the evidence base on intervention effectiveness and the fit with the school or district context, whether they are purchasing a product from vendors or developing it internally. This report provides guidance in the decisionmaking. This report looks…
Descriptors: Decision Making, Intervention, Program Effectiveness, Reading Instruction