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Direct linkSchillinger, Dean; Balyan, Renu; Crossley, Scott A.; McNamara, Danielle S.; Liu, Jennifer Y.; Karter, Andrew J. – Grantee Submission, 2020
Objective: To develop novel, scalable, and valid literacy profiles for identifying limited health literacy patients by harnessing natural language processing. Data Source: With respect to the linguistic content, we analyzed 283 216 secure messages sent by 6941 diabetes patients to physicians within an integrated system's electronic portal.…
Descriptors: Literacy, Profiles, Computational Linguistics, Syntax
Crossley, Scott A.; Allen, Laura K.; McNamara, Danielle S. – Grantee Submission, 2014
The study applied the Multi-Dimensional analysis used by Biber (1988) to examine the functional parameters of essays. Co-occurrence patterns were identified within an essay corpus (n=1529) using a linguistic indices provided by Co-Metrix. These patterns were used to identify essay groups that shared features based upon situational parameters.…
Descriptors: Essays, Writing (Composition), Computational Linguistics, Cues
Crossley, Scott A.; Greenfield, Jerry; McNamara, Danielle S. – TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 2008
Many programs designed to compute the readability of texts are narrowly based on surface-level linguistic features and take too little account of the processes which a reader brings to the text. This study is an exploratory examination of the use of Coh-Metrix, a computational tool that measures cohesion and text difficulty at various levels of…
Descriptors: Reading Comprehension, Readability, Psycholinguistics, Construct Validity
