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Ramotowska, Sonia; Steinert-Threlkeld, Shane; Maanen, Leendert; Szymanik, Jakub – Cognitive Science, 2023
According to logical theories of meaning, a meaning of an expression can be formalized and encoded in truth conditions. Vagueness of the language and individual differences between people are a challenge to incorporate into the meaning representations. In this paper, we propose a new approach to study truth-conditional representations of vague…
Descriptors: Computation, Models, Semantics, Decision Making
Ellana Black; Kristen Betts – Impacting Education: Journal on Transforming Professional Practice, 2025
This convergent mixed methods research study investigated how a small, non-representative sample of Educational Doctorate (EdD) faculty perceive and use generative AI and how they have leveraged the technology to support EdD students. A cross-sectional survey was used to gather data from 27 EdD faculty members to assess their generative AI…
Descriptors: Doctoral Programs, Education Majors, College Faculty, Artificial Intelligence
Ke Li; Lulu Lun; Pingping Hu – Education and Information Technologies, 2025
Amid the ongoing discussion about the potential of LLMs (Large Language Models) to facilitate language learning, there has been a broad spectrum of views in academia. However, little is known about the different viewpoints of students and what contributes to these differences. In light of this, this study adopts Q-methodology, a mixed-methods…
Descriptors: Student Attitudes, Language Attitudes, Affordances, Artificial Intelligence
Carmen Köhler; Johannes Hartig – Contemporary Educational Technology, 2024
Since ChatGPT-3.5 has been available to the public, the potentials and challenges regarding chatbot usage in education have been widely discussed. However, little evidence exists whether and for which purposes students even apply generative AI tools. The first main purpose of the present study was to develop and test scales that assess students'…
Descriptors: Artificial Intelligence, College Students, Natural Language Processing, Technology Uses in Education
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
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
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
Misyak, Jennifer B.; Christiansen, Morten H. – Language Learning, 2012
Although statistical learning and language have been assumed to be intertwined, this theoretical presupposition has rarely been tested empirically. The present study investigates the relationship between statistical learning and language using a within-subject design embedded in an individual-differences framework. Participants were administered…
Descriptors: Comprehension, Sentences, Short Term Memory, Statistics

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