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Forthmann, Boris; Förster, Natalie; Souvignier, Elmar – Journal of Intelligence, 2022
Monitoring the progress of student learning is an important part of teachers' data-based decision making. One such tool that can equip teachers with information about students' learning progress throughout the school year and thus facilitate monitoring and instructional decision making is learning progress assessments. In practical contexts and…
Descriptors: Learning Processes, Progress Monitoring, Robustness (Statistics), Bayesian Statistics
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Carly Oddleifson; Stephen Kilgus; David A. Klingbeil; Alexander D. Latham; Jessica S. Kim; Ishan N. Vengurlekar – Grantee Submission, 2025
The purpose of this study was to conduct a conceptual replication of Pendergast et al.'s (2018) study that examined the diagnostic accuracy of a nomogram procedure, also known as a naive Bayesian approach. The specific naive Bayesian approach combined academic and social-emotional and behavioral (SEB) screening data to predict student performance…
Descriptors: Bayesian Statistics, Accuracy, Social Emotional Learning, Diagnostic Tests
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Solomon, Benjamin G.; Forsberg, Ole J.; Thomas, Monelle; Penna, Brittney; Weisheit, Katherine M. – Assessment for Effective Intervention, 2022
Bayesian regression has emerged as a viable alternative for the estimation of curriculum-based measurement (CBM) growth slopes. Preliminary findings suggest such methods may yield improved efficiency relative to other linear estimators and can be embedded into data management programs for high-frequency use. However, additional research is needed,…
Descriptors: Oral Reading, Reading Fluency, Bayesian Statistics, Accuracy