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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
McLester, Susan – District Administration, 2011
When in 2002 Maine launched its pioneering Maine Learning Technology Initiative (MLTI) that equipped every one of the state's 30,000 seventh- and eighth-grade public school students and teachers with their own Apple iBook, all eyes were on the endeavor. As the first statewide one-to-one deployment, MLTI's $37 million education experiment…
Descriptors: Standardized Tests, Program Effectiveness, Grade 7, Grade 8