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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
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Roscoe, Rod D.; Snow, Erica L.; Brandon, Russell D.; McNamara, Danielle S. – Grantee Submission, 2013
The ability of educational games to promote students' engagement in learning and practice depends on perceived enjoyment of those games. This study investigated high school students' perceptions and enjoyment of games within the Writing Pal intelligent tutoring system. In accord with research on motivation, results showed that perceived…
Descriptors: Educational Games, Educational Technology, Technology Uses in Education, Intelligent Tutoring Systems