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Direct linkSorensen, Lucy C. – Educational Administration Quarterly, 2019
Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…
Descriptors: At Risk Students, Dropouts, Data Collection, Data Analysis
Download full textArizona Department of Education, 2010
As part of compliance with with the federal No Child Left Behind Act, this document presents the State Report Card of Arizona for 2009-2010. The report card provides tables relating to percentage of students who passed AIMS in Arizona by subject and grade. The tables shown in this document include: (1) Mathematics Grade 3; (2) Reading Grade 3; (3)…
Descriptors: Graduation Rate, Definitions, Educational Improvement, Federal Programs
Arizona Department of Education, 2009
The tables presented in this document show the Arizona Instrument to Measure Standards (AIMS) results for the past two years. Twenty-four tables show results as percent at each performance level and percent passing, as well as percent of students tested. The tables shown in this document include: (1) Mathematics Grade 3; (2) Reading Grade 3; (3)…
Descriptors: Report Cards, Grade 8, Grade 7, Grade 6
Neild, Ruth Curran; Balfanz, Robert – Philadelphia Youth Network, 2006
This report uses a unique set of data obtained from the Kids Integrated Data System (KIDS), which is housed at the University of Pennsylvania's Cartographic Modeling Laboratory. The KIDS system merges individual-level data on young people from the School District of Philadelphia and the city's social service agencies, including the Department of…
Descriptors: Dropouts, High School Students, High School Freshmen, Transfer Students
