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Jeremiah T. Stark – ProQuest LLC, 2024
This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…
Descriptors: High School Students, Graduation Rate, Predictor Variables, Predictive Validity
Villanueva, Chandra – Center for Public Policy Priorities, 2017
Roughly defined as grades four through eight, the middle grades are a known pressure point in the educational pipeline -- a make or break period for determining future academic success. Research has shown that students who are not proficient in reading by the beginning of fourth grade are four times more likely to drop out of school. Similarly,…
Descriptors: Middle School Students, Dropouts, Dropout Prevention, Pilot Projects