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Hancock, Gregory R.; An, Ji – Educational Measurement: Issues and Practice, 2018
In this ITEMS module, we frame the topic of scale reliability within a "confirmatory factor analysis" and "structural equation modeling" (SEM) context and address some of the limitations of Cronbach's a. This modeling approach has two major advantages: (1) it allows researchers to make explicit the relation between their items…
Descriptors: Reliability, Structural Equation Models, Factor Analysis, Correlation
Wu, Mike; Davis, Richard L.; Domingue, Benjamin W.; Piech, Chris; Goodman, Noah – International Educational Data Mining Society, 2020
Item Response Theory (IRT) is a ubiquitous model for understanding humans based on their responses to questions, used in fields as diverse as education, medicine and psychology. Large modern datasets offer opportunities to capture more nuances in human behavior, potentially improving test scoring and better informing public policy. Yet larger…
Descriptors: Item Response Theory, Accuracy, Data Analysis, Public Policy
Ravand, Hamdollah – Practical Assessment, Research & Evaluation, 2015
Cognitive diagnostic models (CDM) have been around for more than a decade but their application is far from widespread for mainly two reasons: (1) CDMs are novel, as compared to traditional IRT models. Consequently, many researchers lack familiarity with them and their properties, and (2) Software programs doing CDMs have been expensive and not…
Descriptors: Test Theory, Models, Computer Software, Open Source Technology
Beggrow, Elizabeth P.; Ha, Minsu; Nehm, Ross H.; Pearl, Dennis; Boone, William J. – Journal of Science Education and Technology, 2014
The landscape of science education is being transformed by the new "Framework for Science Education" (National Research Council, "A framework for K-12 science education: practices, crosscutting concepts, and core ideas." The National Academies Press, Washington, DC, 2012), which emphasizes the centrality of scientific…
Descriptors: Science Education, Educational Assessment, Artificial Intelligence, Open Source Technology