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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.; Kim, YouJin – Language Assessment Quarterly, 2019
The current study examined the effects of text-based relational (i.e., cohesion), propositional-specific (i.e., lexical), and syntactic features in a source text on subsequent integration of the source text in spoken responses. It further investigated the effects of word integration on human ratings of speaking performance while taking into…
Descriptors: Individual Differences, Syntax, Oral Language, Speech Communication
Crossley, Scott A.; Kyle, Kristopher; Allen, Laura K.; Guo, Liang; McNamara, Danielle S. – Grantee Submission, 2014
This study investigates the potential for linguistic microfeatures related to length, complexity, cohesion, relevance, topic, and rhetorical style to predict L2 writing proficiency. Computational indices were calculated by two automated text analysis tools (Coh- Metrix and the Writing Assessment Tool) and used to predict human essay ratings in a…
Descriptors: Computational Linguistics, Essays, Scoring, Writing Evaluation
Crossley, Scott A.; Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Journal of Educational Data Mining, 2016
This study investigates a novel approach to automatically assessing essay quality that combines natural language processing approaches that assess text features with approaches that assess individual differences in writers such as demographic information, standardized test scores, and survey results. The results demonstrate that combining text…
Descriptors: Essays, Scoring, Writing Evaluation, Natural Language Processing
Crossley, Scott A.; Allen, David; McNamara, Danielle S. – Language Teaching Research, 2012
Texts are routinely simplified to make them more comprehensible for second language learners. However, the effects of simplification upon the linguistic features of texts remain largely unexplored. Here we examine the effects of one type of text simplification: intuitive text simplification. We use the computational tool, Coh-Metrix, to examine…
Descriptors: Linguistic Input, English (Second Language), Second Language Learning, Intuition
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.; Louwerse, Max M.; McCarthy, Philip M.; McNamara, Danielle S. – Modern Language Journal, 2007
The opinions of second language learning (L2) theorists and researchers are divided over whether to use authentic or simplified reading texts as the means of input for beginning- and intermediate-level L2 learners. Advocates of both approaches cite the use of linguistic features, syntax, and discourse structures as important elements in support of…
Descriptors: Second Language Learning, Syntax, English (Second Language), Language Research
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
