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Ashenafi, Michael Mogessie; Ronchetti, Marco; Riccardi, Giuseppe – International Educational Data Mining Society, 2016
Predicting overall student performance and monitoring progress have attracted more attention in the past five years than before. Demographic data, high school grades and test result constitute much of the data used for building prediction models. This study demonstrates how data from a peer-assessment environment can be used to build student…
Descriptors: Peer Evaluation, Progress Monitoring, Performance, Undergraduate Students
Castellano, Katherine E.; Ho, Andrew D. – Council of Chief State School Officers, 2013
This "Practitioner's Guide to Growth Models," commissioned by the Technical Issues in Large-Scale Assessment (TILSA) and Accountability Systems & Reporting (ASR), collaboratives of the "Council of Chief State School Officers," describes different ways to calculate student academic growth and to make judgments about the…
Descriptors: Guides, Models, Academic Achievement, Achievement Gains
Helping Educators Discuss Responsiveness to Intervention with Parents and Students. Q&A. Winter 2007
Fuchs, Lynn S.; Mellard, Daryl F. – National Research Center on Learning Disabilities, 2007
Responsiveness to intervention (RTI) is proposed as a valuable construct for schools because of its potential utility in providing appropriate learning experiences for all students as well as the early identification of students as being at risk for academic failure. RTI can be conceptualized as providing a framework for systemic reform directed…
Descriptors: Academic Failure, Learning Disabilities, At Risk Students, Response to Intervention