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Sorensen, 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
Colorado Children's Campaign, 2014
"Kids Count in Colorado!" is an annual publication of the Colorado Children's Campaign, which provides the best available state- and county-level data to measure and track the education, health and general well-being of the state's children. "Kids Count in Colorado!" informs policy debates and community discussions, serving as…
Descriptors: Child Health, Well Being, Academic Achievement, Holistic Approach

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