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Zehner, Fabian; Goldhammer, Frank; Lubaway, Emily; Sälzer, Christine – Education Inquiry, 2019
In 2015, the "Programme for International Student Assessment" (PISA) introduced multiple changes in its study design, the most extensive being the transition from paper- to computer-based assessment. We investigated the differences between German students' text responses to eight reading items from the paper-based study in 2012 to text…
Descriptors: Foreign Countries, Achievement Tests, International Assessment, Secondary School Students
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Balling, Laura Winther – Journal of Technical Writing and Communication, 2018
This article considers text comprehension through the integrated perspectives of language processing research and practical writing advice as expressed in writing guides and language policies. Such guides for instance include advice to use active constructions instead of passives and sentences instead of nominalizations. These recommended and…
Descriptors: Reading Comprehension, Regression (Statistics), Language Processing, Writing (Composition)
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Kim, Eun Joo – English Teaching, 2019
Despite the recognized importance of morphological knowledge to literacy outcomes such as vocabulary knowledge and reading comprehension, two of its subconstructs--morphological awareness and morphological processing--have received comparatively little attention. In response, the aim of the study reported here was to examine how the relationships…
Descriptors: Morphology (Languages), Metalinguistics, Grade 10, Vocabulary Development
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Crossley, Scott; Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2015
This study investigates a new approach to automatically assessing essay quality that combines traditional approaches based on assessing textual features with new approaches that measure student attributes such as demographic information, standardized test scores, and survey results. The results demonstrate that combining both text features and…
Descriptors: Automation, Scoring, Essays, Evaluation Methods
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2015
This study builds upon previous work aimed at developing a student model of reading comprehension ability within the intelligent tutoring system, iSTART. Currently, the system evaluates students' self-explanation performance using a local, sentence-level algorithm and does not adapt content based on reading ability. The current study leverages…
Descriptors: Reading Comprehension, Reading Skills, Natural Language Processing, Intelligent Tutoring Systems
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2016
A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the literature on writing. Previous research suggests that higher quality…
Descriptors: Role, Writing (Composition), Natural Language Processing, Hypothesis Testing
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Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Journal of Educational Psychology, 2016
A commonly held belief among educators, researchers, and students is that high-quality texts are easier to read than low-quality texts, as they contain more engaging narrative and story-like elements. Interestingly, these assumptions have typically failed to be supported by the literature on writing. Previous research suggests that higher quality…
Descriptors: Role, Writing (Composition), Natural Language Processing, Hypothesis Testing
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Varner, Laura K.; Jackson, G. Tanner; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2013
This study expands upon an existing model of students' reading comprehension ability within an intelligent tutoring system. The current system evaluates students' natural language input using a local student model. We examine the potential to expand this model by assessing the linguistic features of self-explanations aggregated across entire…
Descriptors: Reading Comprehension, Intelligent Tutoring Systems, Natural Language Processing, Reading Ability
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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
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Snow, Erica L.; Allen, Laura K.; Jacovina, Matthew E.; Crossley, Scott A.; Perret, Cecile A.; McNamara, Danielle S. – Journal of Learning Analytics, 2015
Writing researchers have suggested that students who are perceived as strong writers (i.e., those who generate texts rated as high quality) demonstrate flexibility in their writing style. While anecdotally this has been a commonly held belief among researchers and educators, there is little empirical research to support this claim. This study…
Descriptors: Writing (Composition), Writing Strategies, Hypothesis Testing, Essays
Snow, Erica L.; Allen, Laura K.; Jacovina, Matthew E.; Crossley, Scott A.; Perret, Cecile A.; McNamara, Danielle S. – Grantee Submission, 2015
Writing researchers have suggested that students who are perceived as strong writers (i.e., those who generate texts rated as high quality) demonstrate flexibility in their writing style. While anecdotally this has been a commonly held belief among researchers and educators, there is little empirical research to support this claim. This study…
Descriptors: Writing (Composition), Writing Strategies, Hypothesis Testing, Essays