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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
Westrick, Paul A.; Marini, Jessica P.; Young, Linda; Ng, Helen; Shaw, Emily J. – College Board, 2023
This pilot study examines digital SAT® score relationships with first-year college performance. Results show that digital SAT scores predict college performance as well as paper and pencil SAT scores, and that digital SAT scores meaningfully improve our understanding of a student's readiness for college above high school grade point average…
Descriptors: Computer Assisted Testing, Scores, Career Readiness, College Readiness