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Noa Attali – ProQuest LLC, 2024
In this dissertation, I investigate how people navigate ambiguity in everyday speech, with a focus on quantifier-negation sentences. Combining corpus analysis, behavioral experiments, and computational modeling in the Rational Speech Act framework, I explore preferred interpretations of quantifier-negation and examine the contexts and prosodies…
Descriptors: Language Processing, Ambiguity (Semantics), Intonation, Suprasegmentals
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Sasha Nikolic; Isabelle Wentworth; Lynn Sheridan; Simon Moss; Elisabeth Duursma; Rachel A. Jones; Montserrat Ros; Rebekkah Middleton – Australasian Journal of Educational Technology, 2024
The rapid advancement of artificial intelligence (AI) has outpaced existing research and regulatory frameworks in higher education, leading to varied institutional responses. Although some educators and institutions have embraced AI and generative AI (GenAI), other individuals remain cautious. This systematic literature review explored teaching…
Descriptors: College Faculty, Teacher Attitudes, Intention, Teacher Behavior
Huteng Dai – ProQuest LLC, 2024
In this dissertation, I establish a research program that uses computational modeling as a testbed for theories of phonological learning. This dissertation focuses on a fundamental question: how do children acquire sound patterns from noisy, real-world data, especially in the presence of lexical exceptions that defy regular patterns? For instance,…
Descriptors: Phonology, Language Acquisition, Computational Linguistics, Linguistic Theory
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Sarah Berger; Laura J. Batterink – Developmental Science, 2024
Children achieve better long-term language outcomes than adults. However, it remains unclear whether children actually learn language "more quickly" than adults during real-time exposure to input--indicative of true superior language learning abilities--or whether this advantage stems from other factors. To examine this issue, we…
Descriptors: Child Language, Language Acquisition, Learning Processes, Language Skills
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Anthony G. Picciano – Online Learning, 2024
Artificial intelligence (AI) has been evolving since the mid-twentieth-century when luminaries such as Alan Turing, Herbert Simon, and Marvin Minsky began developing rudimentary AI applications. For decades, AI programs remained pretty much in the realm of computer science and experimental game playing. This changed radically in the 2020s when…
Descriptors: Teacher Education, Seminars, Technology Uses in Education, Artificial Intelligence
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Alaa Alzahrani; Hanan Almalki – Asian-Pacific Journal of Second and Foreign Language Education, 2024
A robust finding in psycholinguistics is that prior language experience influences subsequent language processing. This phenomenon is known as syntactic priming. Most of the empirical support for L2 syntactic priming comes from lab-based experiments. However, this evidence might not reflect how priming occurs in typical language activities in the…
Descriptors: Second Language Instruction, Arabic, Oral Reading, Story Reading
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Judith F. Kroll; Paola E. Dussias – Language Teaching Research Quarterly, 2024
In the history of psycholinguistics, there are traditional accounts that have been told about language learning and processing. These accounts revolve around the constraints imposed by the age of language learning and by universal principles that are assumed to be natively given. The contribution of Brian MacWhinney and his collaborators has been…
Descriptors: Transfer of Training, Bilingualism, Native Language, Second Language Learning
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Peel, Hayden J.; Royals, Kayla A.; Chouinard, Philippe A. – Journal of Psycholinguistic Research, 2022
It is widely assumed that subliminal word priming is case insensitive and that a short SOA (< 100 ms) is required to observe any effects. Here we attempted to replicate results from an influential study with the inclusion of a longer SOA to re-examine these assumptions. Participants performed a semantic categorisation task on visible word…
Descriptors: Priming, Psycholinguistics, Reaction Time, Semantics
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Kocab, Annemarie; Davidson, Kathryn; Snedeker, Jesse – Cognitive Science, 2022
Classical quantifiers (like "all," "some," and "none") express relationships between two sets, allowing us to make generalizations (like "no elephants fly"). Devices like these appear to be universal in human languages. Is the ubiquity of quantification due to a universal property of the human mind or is it…
Descriptors: Natural Language Processing, Form Classes (Languages), Cognitive Processes, Spanish
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He, Angela Xiaoxue – Infant and Child Development, 2022
In acquiring a native language, the input children receive, to an unneglectable extent, shapes the rate of acquisition and the ultimate achievement. This in turn has cascading effects on many aspects of later development, including but not limited to language. Providing optimal input for early language development, therefore, is of major interest…
Descriptors: Linguistic Input, Native Language, Language Acquisition, Memory
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Kalandadze, Tamara; Braeken, Johan; Brynskov, Cecilia; Naess, Kari-Anne Bottegaard – Journal of Autism and Developmental Disorders, 2022
Poor metaphor comprehension was considered a hallmark of autism spectrum disorder (ASD), but recent research has questioned the extent and the sources of these difficulties. In this cross-sectional study, we compared metaphor comprehension in individuals with ASD (N = 29) and individuals with typical development (TD; N = 31), and investigated the…
Descriptors: Figurative Language, Language Processing, Comprehension, Language Skills
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Brown, Violet A.; Fox, Neal P.; Strand, Julia F. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
Listeners make use of contextual cues during continuous speech processing that help overcome the limitations of the acoustic input. These semantic, grammatical, and pragmatic cues facilitate prediction of upcoming words and/or reduce the lexical search space by inhibiting activation of contextually inappropriate words that share phonological…
Descriptors: Cues, Language Processing, Grammar, Sentence Structure
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Bulut, Okan; Yildirim-Erbasli, Seyma Nur – International Journal of Assessment Tools in Education, 2022
Reading comprehension is one of the essential skills for students as they make a transition from learning to read to reading to learn. Over the last decade, the increased use of digital learning materials for promoting literacy skills (e.g., oral fluency and reading comprehension) in K-12 classrooms has been a boon for teachers. However, instant…
Descriptors: Reading Comprehension, Natural Language Processing, Artificial Intelligence, Automation
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Anson, Chris M. – Composition Studies, 2022
Student plagiarism has challenged educators for decades, with heightened paranoia following the advent of the Internet in the 1980's and ready access to easily copied text. But plagiarism will look like child's play next to new developments in AI-based natural-language processing (NLP) systems that increasingly appear to "write" as…
Descriptors: Plagiarism, Artificial Intelligence, Natural Language Processing, Writing Assignments
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Chantavarin, Suphasiree; Morgan, Emily; Ferreira, Fernanda – Cognitive Science, 2022
Prior research has shown that various types of conventional multiword chunks are processed faster than matched novel strings, but it is unclear whether this processing advantage extends to variant multiword chunks that are less formulaic. To determine whether the processing advantage of multiword chunks accommodates variations in the canonical…
Descriptors: Eye Movements, Form Classes (Languages), Cognitive Ability, Language Processing
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