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Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – Grantee Submission, 2024
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change
Crossley, Scott A.; Skalicky, Stephen; Dascalu, Mihai; McNamara, Danielle S.; Kyle, Kristopher – Discourse Processes: A multidisciplinary journal, 2017
Research has identified a number of linguistic features that influence the reading comprehension of young readers; yet, less is known about whether and how these findings extend to adult readers. This study examines text comprehension, processing, and familiarity judgment provided by adult readers using a number of different approaches (i.e.,…
Descriptors: Reading Processes, Reading Comprehension, Readability, Adults
Crossley, Scott A.; Allen, David B.; McNamara, Danielle S. – Reading in a Foreign Language, 2011
Texts are routinely simplified for language learners with authors relying on a variety of approaches and materials to assist them in making the texts more comprehensible. Readability measures are one such tool that authors can use when evaluating text comprehensibility. This study compares the Coh-Metrix Second Language (L2) Reading Index, a…
Descriptors: Readability, Readability Formulas, Word Processing, Psycholinguistics