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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
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Cratty, Dorothyjean – Economics of Education Review, 2012
Nineteen percent of 1997-98 North Carolina 3rd graders were observed to drop out of high school. A series of logits predict probabilities of dropping out on determinants such as math and reading test scores, absenteeism, suspension, and retention, at the following grade levels: 3rd, 5th, 8th, and 9th. The same cohort and variables are used to…
Descriptors: At Risk Students, Dropouts, High School Students, Probability
Daniels, Byron L. – ProQuest LLC, 2010
The home and the public school classroom have been key environments in the African American community and have been instrumental in developing identity and encouraging academic progress. Despite this, the dropout rates of African American males in secondary grades have increased, while academic achievement scores of African American males in the…
Descriptors: Achievement Gap, African American Community, Public Schools, Self Concept