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Hadis Anahideh; Nazanin Nezami; Abolfazl Asudeh – Grantee Submission, 2025
It is of critical importance to be aware of the historical discrimination embedded in the data and to consider a fairness measure to reduce bias throughout the predictive modeling pipeline. Given various notions of fairness defined in the literature, investigating the correlation and interaction among metrics is vital for addressing unfairness.…
Descriptors: Correlation, Measurement Techniques, Guidelines, Semantics
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Elliott Ostler; Tami Williams; John Schultz – School Leadership Review, 2025
In today's data-driven and data-informed educational landscape, leaders face increasing pressure to make decisions and present results based on what appear to be comprehensive statistical analyses. However, the ethical implications of these responsibilities can be complex, particularly when statistical results carry the potential to be…
Descriptors: Data Analysis, Statistical Analysis, Data Use, Ethics
Victoria L. Bernhardt – Eye on Education, 2025
With the 5th Edition of Data Analysis for Continuous School Improvement, best-selling Victoria Bernhardt has written the go-to-resource for data analysis in your school! By incorporating collaborative structures to implement, monitor, and evaluate the vision and continuous improvement plan, this book provides a framework to show learning…
Descriptors: Learning Analytics, Data Analysis, Educational Improvement, Evaluation Methods
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Sheryl S. Lazarus; Martha L. Thurlow; Mari K. A. Quanbeck – Journal of Special Education, 2025
The 2015 reauthorization of the Elementary and Secondary Education Act placed a 1.0% cap on the participation of students with disabilities in the alternate assessment based on alternate academic achievement standards (AA-AAAS). U.S. Department of Education regulations clarified that states must develop participation guidelines and a definition of…
Descriptors: Students with Disabilities, Alternative Assessment, Guidelines, State Standards