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Tianlong Zhong; Gaoxia Zhu; Chenyu Hou; Yuhan Wang; Xiuyi Fan – Education and Information Technologies, 2024
The significance of interdisciplinary learning has been well-recognized by higher education institutions. However, when teaching interdisciplinary learning to junior undergraduate students, their limited disciplinary knowledge and underrepresentation of students from some disciplines can hinder their learning performance. ChatGPT's ability to…
Descriptors: Influences, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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Ibrahim Adeshola; Adeola Praise Adepoju – Interactive Learning Environments, 2024
The launch of OpenAI ChatGPT's language-generation model has raised alarms within many sectors, especially the academic sector. Several academicians have urged universities to develop new forms of assessment after the launch of ChatGPT, which solves academic questions in less than a few minutes. Academic cheating is not a new phenomenon, and the…
Descriptors: Opportunities, Barriers, Artificial Intelligence, Natural Language Processing
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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Tal Waltzer; Celeste Pilegard; Gail D. Heyman – International Journal for Educational Integrity, 2024
The release of ChatGPT in 2022 has generated extensive speculation about how Artificial Intelligence (AI) will impact the capacity of institutions for higher learning to achieve their central missions of promoting learning and certifying knowledge. Our main questions were whether people could identify AI-generated text and whether factors such as…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, College Students
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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
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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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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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
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Ryusei Munemura; Fumiya Okubo; Tsubasa Minematsu; Yuta Taniguchi; Atsushi Shimada – International Association for Development of the Information Society, 2024
Course planning is essential for academic success and the achievement of personal goals. Although universities provide course syllabi and curriculum maps for course planning, integrating and understanding these resources by the learners themselves for effective course planning is time-consuming and difficult. To address this issue, this study…
Descriptors: Curriculum Development, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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Lancaster, Thomas – Journal of Academic Ethics, 2021
Is academic integrity research presented from a positive integrity standpoint? This paper uses Natural Language Processing (NLP) techniques to explore a data set of 8,507 academic integrity papers published between 1904 and 2019.Two main techniques are used to linguistically examine paper titles: (1) bigram (word pair) analysis and (2) sentiment…
Descriptors: Cheating, Integrity, Natural Language Processing, Educational Research
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Gambi, Chiara; Jindal, Priya; Sharpe, Sophie; Pickering, Martin J.; Rabagliati, Hugh – Child Development, 2021
By age 2, children are developing foundational language processing skills, such as quickly recognizing words and predicting words before they occur. How do these skills relate to children's structural knowledge of vocabulary? Multiple aspects of language processing were simultaneously measured in a sample of 2-to-5-year-olds (N = 215): While older…
Descriptors: Preschool Children, Vocabulary Development, Ability, Prediction
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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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