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Download full textBosch, Nigel – Journal of Educational Data Mining, 2021
Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…
Descriptors: Accuracy, Learning Analytics, Models, National Competency Tests
Shyjka, Andria; Gutiérrez, Vanessa; Hinton, Ebony – University of Chicago Consortium on School Research, 2020
Responding to an Illinois law that took effect in 2010, the Performance Evaluation Reform Act (PERA), Chicago Public Schools (CPS) created and implemented the REACH (Recognizing Educators Advancing Chicago's Students) educator evaluation and support system. REACH was piloted in 2012-13. It is still being implemented as of the 2019-20 school year,…
Descriptors: Teacher Evaluation, Evaluation Methods, Value Added Models, Public Schools
Kelcey, Ben; Wang, Shanshan; Cox, Kyle – Society for Research on Educational Effectiveness, 2016
Valid and reliable measurement of unobserved latent variables is essential to understanding and improving education. A common and persistent approach to assessing latent constructs in education is the use of rater inferential judgment. The purpose of this study is to develop high-dimensional explanatory random item effects models designed for…
Descriptors: Test Items, Models, Evaluators, Longitudinal Studies
