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Li, Haiying; Graesser, Arthur C. – Journal of Research on Technology in Education, 2021
This study investigated how computer agents' language style affects summary writing in an Intelligent Tutoring System, called CSAL AutoTutor. Participants interacted with two computer agents in one of three language styles: (1) a "formal" language style, (2) an "informal" language style, and (3) a "mixed" language…
Descriptors: Intelligent Tutoring Systems, Language Styles, Writing (Composition), Writing Improvement
McNamara, Danielle S.; Graesser, Arthur C.; McCarthy, Philip M.; Cai, Zhiqiang – Cambridge University Press, 2014
Coh-Metrix is among the broadest and most sophisticated automated textual assessment tools available today. Automated Evaluation of Text and Discourse with Coh-Metrix describes this computational tool, as well as the wide range of language and discourse measures it provides. Section I of the book focuses on the theoretical perspectives that led to…
Descriptors: Writing Evaluation, Computational Linguistics, Connected Discourse, Data Analysis
Li, Haiying; Graesser, Arthur C.; Conley, Mark; Cai, Zhiqiang; Pavlik, Philip I., Jr.; Pennebaker, James W. – Discourse Processes: A multidisciplinary journal, 2016
Formality has long been of interest in the study of discourse, with periodic discussions of the best measure of formality and the relationship between formality and text categories. In this research, we explored what features predict formality as humans perceive the construct. We categorized a corpus consisting of 1,158 discourse samples published…
Descriptors: Discourse Analysis, Computational Linguistics, Comparative Analysis, Speeches
Graesser, Arthur C.; McNamara, Danielle S.; Cai, Zhiqang; Conley, Mark; Li, Haiying; Pennebaker, James – Elementary School Journal, 2014
Coh-Metrix analyzes texts on multiple measures of language and discourse that are aligned with multilevel theoretical frameworks of comprehension. Dozens of measures funnel into five major factors that systematically vary as a function of types of texts (e.g., narrative vs. informational) and grade level: narrativity, syntactic simplicity, word…
Descriptors: Statistical Analysis, Guidelines, Syntax, Reading Comprehension
Graesser, Arthur C.; McNamara, Danielle S.; Cai, Zhiqiang; Conley, Mark; Li, Haiying; Pennebaker, James – Grantee Submission, 2014
Coh-Metrix analyzes texts on multiple measures of language and discourse that are aligned with multilevel theoretical frameworks of comprehension. Dozens of measures funnel into five major factors that systematically vary as a function of types of texts (e.g., narrative vs. informational) and grade level: narrativity, syntactic simplicity, word…
Descriptors: Statistical Analysis, Guidelines, Syntax, Reading Comprehension
Medimorec, Srdan; Pavlik, Philip I., Jr.; Olney, Andrew; Graesser, Arthur C.; Risko, Evan F. – Journal of Educational Psychology, 2015
Recent studies have used Coh-Metrix, an automated text analyzer, to assess differences in language characteristics across different genres and academic disciplines (Graesser, McNamara, & Kulikowich, 2011; McNamara, Graesser, McCarthy, & Cai, 2014). Coh-Metrix analyzes text on many constructs at different levels, including Word Concreteness…
Descriptors: Language of Instruction, Lecture Method, Oral Language, Language Usage
McNamara, Danielle S.; Louwerse, Max M.; McCarthy, Philip M.; Graesser, Arthur C. – Discourse Processes: A Multidisciplinary Journal, 2010
This study addresses the need in discourse psychology for computational techniques that analyze text on multiple levels of cohesion and text difficulty. Discourse psychologists often investigate phenomena related to discourse processing using lengthy texts containing multiple paragraphs, as opposed to single word and sentence stimuli.…
Descriptors: Computational Linguistics, Connected Discourse, Difficulty Level, Rhetoric

Haberlandt, Karl; Graesser, Arthur C. – Discourse Processes, 1989
Describes two subject-paced reading experiments in which word-reading times were collected using the moving-window method. Finds that reading times of content words increase more steeply than reading times for function words. Discusses results in terms of buffer models of reading, the processing of different lexical classes, and hypotheses which…
Descriptors: Associative Learning, Connected Discourse, Context Clues, Function Words