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Showing 1 to 15 of 17 results Save | Export
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Wesley Morris; Scott Crossley; Langdon Holmes; Chaohua Ou; Mihai Dascalu; Danielle McNamara – International Journal of Artificial Intelligence in Education, 2025
As intelligent textbooks become more ubiquitous in classrooms and educational settings, the need to make them more interactive arises. An alternative is to ask students to generate knowledge in response to textbook content and provide feedback about the produced knowledge. This study develops Natural Language Processing models to automatically…
Descriptors: Formative Evaluation, Feedback (Response), Textbooks, Artificial Intelligence
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Muhammad Mooneeb Ali; Ahmed M. Alaa; Wael Alharbi; Issa Al Qurashi – International Journal of Technology in Education, 2025
Machine and prompt-based Artificial Intelligence (AI) learning has made significant evolution profusely. In education, it has revitalized researchers and educators to scout out subsequent advantages for optimizing learning results. Chiefly, Generative AI has exhibited substantial potential as a tool for language augmentation. This study aims to…
Descriptors: Foreign Countries, Grade 10, Artificial Intelligence, Natural Language Processing
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Allen, Laura Kristen; Magliano, Joseph P.; McCarthy, Kathryn S.; Sonia, Allison N.; Creer, Sarah D.; McNamara, Danielle S. – Grantee Submission, 2021
The current study examined the extent to which the cohesion detected in readers' constructed responses to multiple documents was predictive of persuasive, source-based essay quality. Participants (N=95) completed multiple-documents reading tasks wherein they were prompted to think-aloud, self-explain, or evaluate the sources while reading a set of…
Descriptors: Reading Comprehension, Connected Discourse, Reader Response, Natural Language Processing
Sonia, Allison N.; Joseph, Magliano P.; McCarthy, Kathryn S.; Creer, Sarah D.; McNamara, Danielle S.; Allen, Laura K. – Grantee Submission, 2022
The constructed responses individuals generate while reading can provide insights into their coherence-building processes. The current study examined how the cohesion of constructed responses relates to performance on an integrated writing task. Participants (N = 95) completed a multiple document reading task wherein they were prompted to think…
Descriptors: Natural Language Processing, Connected Discourse, Reading Processes, Writing Skills
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Sonia, Allison N.; Magliano, Joseph P.; McCarthy, Kathryn S.; Creer, Sarah D.; McNamara, Danielle S.; Allen, Laura, K. – Discourse Processes: A Multidisciplinary Journal, 2022
The constructed responses individuals generate while reading can provide insights into their coherence-building processes. The current study examined how the cohesion of constructed responses relates to performance on an integrated writing task. Participants (N = 95) completed a multiple document reading task wherein they were prompted to think…
Descriptors: Natural Language Processing, Connected Discourse, Reading Processes, Writing Skills
Tamara P. Tate; Young-Suk Grace Kim; Penelope Collins; Mark Warschauer; Carol Booth Olson – Written Communication, 2024
This article provides three major contributions to the literature: we provide granular information on the development of student argumentative writing across secondary school; we replicate the MacArthur et al. model of Natural Language Processing (NLP) writing features that predict quality with a younger group of students; and we are able to…
Descriptors: Gender Differences, Reading Comprehension, Reading Fluency, Essays
Allen, Laura K.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2018
The assessment of writing proficiency generally includes analyses of the specific linguistic and rhetorical features contained in the singular essays produced by students. However, researchers have recently proposed that an individual's ability to flexibly adapt the linguistic properties of their writing might more closely capture writing skill.…
Descriptors: Writing Evaluation, Writing Tests, Computer Assisted Testing, Writing Skills
Allen, Laura K.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2018
The assessment of argumentative writing generally includes analyses of the specific linguistic and rhetorical features contained in the individual essays produced by students. However, researchers have recently proposed that an individual's ability to flexibly adapt the linguistic properties of their writing may more accurately capture their…
Descriptors: Writing (Composition), Persuasive Discourse, Essays, Language Usage
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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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
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Jacovina, Matthew E.; McNamara, Danielle S. – Grantee Submission, 2017
In this chapter, we describe several intelligent tutoring systems (ITSs) designed to support student literacy through reading comprehension and writing instruction and practice. Although adaptive instruction can be a powerful tool in the literacy domain, developing these technologies poses significant challenges. For example, evaluating the…
Descriptors: Intelligent Tutoring Systems, Literacy Education, Educational Technology, Technology Uses in Education
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