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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
McNamara, Danielle S.; Jacovina, Matthew E.; Snow, Erica L.; Allen, Laura K. – Grantee Submission, 2015
Work in cognitive and educational psychology examines a variety of phenomena related to the learning and retrieval of information. Indeed, Alice Healy, our honoree, and her colleagues have conducted a large body of groundbreaking research on this topic. In this article we discuss how 3 learning principles (the generation effect, deliberate…
Descriptors: Learning Processes, Instructional Design, Intelligent Tutoring Systems, Writing Instruction
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
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Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2014
In the current study, we utilize natural language processing techniques to examine relations between the linguistic properties of students' self-explanations and their reading comprehension skills. Linguistic features of students' aggregated self-explanations were analyzed using the Linguistic Inquiry and Word Count (LIWC) software. Results…
Descriptors: Natural Language Processing, Reading Comprehension, Linguistics, Predictor Variables
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