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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
Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables
Backes, Ben; Cowan, James – National Center for Analysis of Longitudinal Data in Education Research (CALDER), 2020
Prior work has documented a substantial penalty associated with taking the Partnership for Assessment of Readiness for College and Careers (PARCC) online relative to on paper (Backes & Cowan, 2019). However, this penalty does not necessarily make online tests less useful. For example, it could be the case that computer literacy skills are…
Descriptors: Predictive Validity, Test Validity, Computer Assisted Testing, Comparative Analysis
Peltier, Corey; Vannest, Kimberly J.; Tomaszewski, Brianne R.; Morin, Kristi; Sallese, Mary Rose; Pulos, Joshua M. – Exceptionality, 2022
The current study examined the criterion validity of a computer adaptive universal screener with an end-of-year state mathematics assessment using extant data provided by a local education agency. Participants included 1,195 third through eighth graders. Correlational analyses were used to report predictive and concurrent validity coefficients for…
Descriptors: Adaptive Testing, Computer Assisted Testing, Screening Tests, Mathematics Tests
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
Porter, Tenelle; Molina, Diego Catalán; Blackwell, Lisa; Roberts, Sylvia; Quirk, Abigail; Duckworth, Angela L.; Trzesniewski, Kali – Journal of Learning Analytics, 2020
Mastery behaviours -- seeking out challenging tasks and continuing to work on them despite difficulties -- are integral to achievement but difficult to measure with precision. The current study reports on the development and validation of the computer-based persistence, effort, resilience, and challenge-seeking (PERC) task in two demographically…
Descriptors: Mastery Learning, Resilience (Psychology), Difficulty Level, Computer Assisted Instruction