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Anika Alam; A. Brooks Bowden – Society for Research on Educational Effectiveness, 2024
Background: The importance of high school completion for jobs and postsecondary opportunities is well- documented. Combined with federal laws where high school graduation rate is a core performance indicator, school systems and states face pressure to actively monitor and assess high school completion. This proposal employs machine learning…
Descriptors: Dropout Characteristics, Prediction, Artificial Intelligence, At Risk Students
Brunner, Josie; Malerba, Cathy – Online Submission, 2010
This research brief provides highlights from the full report (published separately). In the report on AISD students, with a focus on the graduating class of 2009, the most powerful predictors of overall student dropout risk were having an 8th-grade attendance rate of less than 90% and failing both the 8th-grade reading and math TAKS tests. [For…
Descriptors: Grade 8, Predictor Variables, Dropout Characteristics, Dropouts
Brunner, Josie; Malerba, Cathy – Online Submission, 2009
In this report on AISD students, with a focus on the graduating class of 2009, the most powerful predictors of overall student dropout risk were having an 8th-grade attendance rate of less than 90% and failing both the 8th-grade reading and math TAKS tests. A separate research brief also was published. [For the research brief, see ED628171.]
Descriptors: Grade 8, Predictor Variables, Dropout Characteristics, Dropouts
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