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Showing 31 to 45 of 1,116 results Save | Export
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Thornton, Chris – Cognitive Science, 2021
Semantic composition in language must be closely related to semantic composition in thought. But the way the two processes are explained differs considerably. Focusing primarily on propositional content, language theorists generally take semantic composition to be a truth-conditional process. Focusing more on extensional content, cognitive…
Descriptors: Semantics, Cognitive Processes, Linguistic Theory, Language Usage
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Baggio, Giosuè – Cognitive Science, 2021
Compositionality has been a central concept in linguistics and philosophy for decades, and it is increasingly prominent in many other areas of cognitive science. Its status, however, remains contentious. Here, I reassess the nature and scope of the principle of compositionality (Partee, 1995) from the perspective of psycholinguistics and cognitive…
Descriptors: Language Processing, Psycholinguistics, Neurosciences, Phrase Structure
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Phan, Lee; Tariq, Alina; Lam, Garbo; Pang, Elizabeth W.; Alain, Claude – Journal of Autism and Developmental Disorders, 2021
Semantic processing impairments are present in a proportion of individuals with autism spectrum disorder (ASD). Despite the numerous imaging studies investigating this language domain in ASD, there is a lack of consensus regarding the brain structures showing abnormal pattern of activity. This meta-analysis aimed to identify neural activation…
Descriptors: Autism, Pervasive Developmental Disorders, Semantics, Language Processing
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Parks, Louisa; Peters, Wim – International Journal of Social Research Methodology, 2023
The ever-increasing application of Digital Humanities techniques to social scientific research questions calls for continuous reflection on how they can contribute to scholarly research in combination with other more common text analysis methods. This article explores the various dimensions along which scholarly text analysis can be performed,…
Descriptors: Natural Language Processing, Humanities, Social Science Research, Content Analysis
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Matthew Landers – Higher Education for the Future, 2025
This article presents a brief overview of the state-of-the-art in large language models (LLMs) like ChatGPT and discusses the difficulties that these technologies create for educators with regard to assessment. Making use of the 'arms race' metaphor, this article argues that there are no simple solutions to the 'AI problem'. Rather, this author…
Descriptors: Ethics, Cheating, Plagiarism, Artificial Intelligence
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Nivja H. de Jong – Language Teaching Research Quarterly, 2023
In current research into second language (L2) speaking, aspects of fluency are measured as static constructs. Averaged over a complete speaking performance, for instance, syllables per minute is calculated. Similarly, the number of pauses is calculated per minute, averaged over a complete speaking task. This paper argues, however, that we need to…
Descriptors: Speech Communication, Language Fluency, Second Language Learning, Second Language Instruction
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Dianova, Vera G.; Schultz, Mario D. – Industry and Higher Education, 2023
This comment builds on the example of chat generative pretrained transformer (ChatGPT) to discuss the implications of generative AI on industry and higher education, underlining the need for more transdisciplinary digital literacy education. The release of ChatGPT has generated significant academic and professional interest and instigated a…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Industry
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Günther, Fritz; Marelli, Marco – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2019
Effects of semantic transparency, reflected in processing differences between semantically transparent ("teabag") and opaque ("ladybird") compounds, have received considerable attention in the investigation of the role of constituents in compound processing. However, previous studies have yielded inconsistent results. In the…
Descriptors: Semantics, Language Processing, Vocabulary, Definitions
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Debby R. E. Cotton; Peter A. Cotton; J. Reuben Shipway – Innovations in Education and Teaching International, 2024
The use of artificial intelligence in academia is a hot topic in the education field. ChatGPT is an AI tool that offers a range of benefits, including increased student engagement, collaboration, and accessibility. However, is also raises concerns regarding academic honesty and plagiarism. This paper examines the opportunities and challenges of…
Descriptors: Integrity, Cheating, Artificial Intelligence, Man Machine Systems
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Daniela Fontenelle-Tereshchuk – Discover Education, 2024
This paper reflects on an educator's perceived experiences and observations on the complex process of 'passage' when students transitioning from high school into their first-year of post-secondary education often struggle to adapt to academic writing standards. It relies on literature to further explore such a process. Written communication has…
Descriptors: Writing (Composition), Artificial Intelligence, Technology Uses in Education, Natural Language Processing
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Danielle A. Waterfield; Latesha Watson; Jamie Day – Journal of Special Education Technology, 2024
Artificial intelligence (AI) has been rapidly developing, both in the education field and beyond, in recent years. Due to this fast-paced nature, special education teachers may not be aware of the availability of AI that could be pertinent to their practice. In this manuscript, five AI platforms that are readily available for special education…
Descriptors: Artificial Intelligence, Special Education, Educational Technology, Teaching Methods
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Austin Pack; Jeffrey Maloney – TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 2024
While recent and significant progress made in natural language processing and artificial intelligence (AI) has the potential to drastically influence the field of language education, many language educators and administrators remain unfamiliar with these recent technological advances and their pedagogical implications. The primary purpose of this…
Descriptors: Artificial Intelligence, English (Second Language), Natural Language Processing, Language Teachers
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Maria Goldshtein; Jaclyn Ocumpaugh; Andrew Potter; Rod D. Roscoe – Grantee Submission, 2024
As language technologies have become more sophisticated and prevalent, there have been increasing concerns about bias in natural language processing (NLP). Such work often focuses on the effects of bias instead of sources. In contrast, this paper discusses how normative language assumptions and ideologies influence a range of automated language…
Descriptors: Language Attitudes, Computational Linguistics, Computer Software, Natural Language Processing
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Mahowald, Kyle; Kachergis, George; Frank, Michael C. – First Language, 2020
Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…
Descriptors: Models, Language Processing, Computational Linguistics, Language Acquisition
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Chau, Hung; Labutov, Igor; Thaker, Khushboo; He, Daqing; Brusilovsky, Peter – International Journal of Artificial Intelligence in Education, 2021
The increasing popularity of digital textbooks as a new learning media has resulted in a growing interest in developing a new generation of "adaptive textbooks" that can help readers to learn better through adapting to the readers' learning goals and the current state of knowledge. These adaptive textbooks are most frequently powered by…
Descriptors: Automation, Textbooks, Computer Uses in Education, Artificial Intelligence
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