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Sinclair, Jeanne; Jang, Eunice Eunhee; Rudzicz, Frank – Journal of Educational Psychology, 2021
Advances in machine learning (ML) are poised to contribute to our understanding of the linguistic processes associated with successful reading comprehension, which is a critical aspect of children's educational success. We used ML techniques to investigate and compare associations between children's reading comprehension and 260 linguistic…
Descriptors: Prediction, Reading Comprehension, Natural Language Processing, Speech Communication
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Olney, Andrew M.; Pavlik, Philip I., Jr.; Maass, Jaclyn K. – Grantee Submission, 2017
This study investigated the effect of cloze item practice on reading comprehension, where cloze items were either created by humans, by machine using natural language processing techniques, or randomly. Participants from Amazon Mechanical Turk (N = 302) took a pre-test, read a text, and took part in one of five conditions, Do-Nothing, Re-Read,…
Descriptors: Reading Improvement, Reading Comprehension, Prior Learning, Cloze Procedure
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Biemiller, Andrew; Rosenstein, Mark; Sparks, Randall; Landauer, Thomas K.; Foltz, Peter W. – Scientific Studies of Reading, 2014
Determining word meanings that ought to be taught or introduced is important for educators. A sequence for vocabulary growth can be inferred from many sources, including testing children's knowledge of word meanings at various ages, predicting from print frequency, or adult-recalled Age of Acquisition. A new approach, Word Maturity, is based on…
Descriptors: Foreign Countries, Vocabulary Development, Natural Language Processing, Word Frequency