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Ben Seipel; Sarah E. Carlson; Virginia Clinton-Lisell; Mark L. Davison; Patrick C. Kennedy – Grantee Submission, 2022
Originally designed for students in Grades 3 through 5, MOCCA (formerly the Multiple-choice Online Causal Comprehension Assessment), identifies students who struggle with comprehension, and helps uncover why they struggle. There are many reasons why students might not comprehend what they read. They may struggle with decoding, or reading words…
Descriptors: Multiple Choice Tests, Computer Assisted Testing, Diagnostic Tests, Reading Tests
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Carlson, Sarah E.; Seipel, Ben; Biancarosa, Gina; Davison, Mark L.; Clinton, Virginia – Grantee Submission, 2019
This demonstration introduces and presents an innovative online cognitive diagnostic assessment, developed to identify the types of cognitive processes that readers use during comprehension; specifically, processes that distinguish between subtypes of struggling comprehenders. Cognitive diagnostic assessments are designed to provide valuable…
Descriptors: Reading Comprehension, Standardized Tests, Diagnostic Tests, Computer Assisted Testing
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Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use