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Mary Kalantzis; Bill Cope – Reading Research Quarterly, 2025
The latest mutation of Artificial Intelligence, Generative AI, is more than anything a technology of writing. It is a machine that can write. In a world-historical frame, the significance of this cannot be understated. This is a technology in which the unnatural language of code tangles with the natural language of everyday life. Its form of…
Descriptors: Artificial Intelligence, Natural Language Processing, Literacy Education, Technology Uses in Education
Ainhoa Berciano; Astrid Cuida; María-Luisa Novo – Education and Information Technologies, 2025
In the last two decades, computational thinking has gained wide relevance in international educational systems. The inclusion of this new type of thinking poses educational challenges with some underlying research questions that need to be answered to meet these challenges with quality. Thus, this study focuses on analyzing the difficulties that…
Descriptors: Coding, Translation, Programming Languages, Sequential Approach
Nina Schoener; Sara C. Johnson; Sumarga H. Suanda – Cognitive Science, 2025
Both classic thought experiments and recent empirical evidence suggest that children frequently encounter new words whose meanings are underdetermined by the extralinguistic contexts in which they occur. The role that these referentially ambiguous events play in children's word learning is central to ongoing debates in the field. Do children learn…
Descriptors: Vocabulary Development, Semantics, Ambiguity (Semantics), Metalinguistics
Fan Zhang; Chenglu Li; Owen Henkel; Wanli Xing; Sami Baral; Neil Heffernan; Hai Li – International Journal of Artificial Intelligence in Education, 2025
In recent years, the pre-training of Large Language Models (LLMs) in the educational domain has garnered significant attention. However, a discernible gap exists in the application of these models to mathematics education. This study aims to bridge this gap by pre-training LLMs on authentic K-12 mathematical dialogue datasets. Our research is…
Descriptors: Artificial Intelligence, Natural Language Processing, Mathematics Education, Elementary Secondary Education
James Edward Hill; Catherine Harris; Andrew Clegg – Research Synthesis Methods, 2024
Data extraction is a time-consuming and resource-intensive task in the systematic review process. Natural language processing (NLP) artificial intelligence (AI) techniques have the potential to automate data extraction saving time and resources, accelerating the review process, and enhancing the quality and reliability of extracted data. In this…
Descriptors: Artificial Intelligence, Search Engines, Data Collection, Natural Language Processing
Brent Archer; Marion C. Leaman; Zaneta Mok – Topics in Language Disorders, 2024
People with aphasia may produce speech errors or pauses during speaking turns. A communication partner may choose to guess the person's intended meaning, or may allow the person time to repair their turns (i.e., edited turns). The aim of this study was to understand the topic-related effects that occur when speakers without aphasia allow their…
Descriptors: Aphasia, Interpersonal Communication, Dialogs (Language), Speech Communication
Alexandra Krauska – ProQuest LLC, 2024
In standard models of language production or comprehension, the elements which are retrieved from memory and combined into a syntactic structure are "lemmas" or "lexical items". Such models implicitly take a "lexicalist" approach, which assumes that lexical items store meaning, syntax, and form together, that…
Descriptors: Lexicology, Syntax, Neurolinguistics, Language Processing
Linrui Yang; Yue Mu; Yuxiang Zhai; Renji Chen – International Journal of Language & Communication Disorders, 2024
Background: Cleft lip and palate is one of the most common oral and maxillofacial deformities associated with a variety of functional disorders. Cleft palate speech disorder (CPSD) occurs the most frequently and manifests a series of characteristic speech features, which are called cleft speech characteristics. Some scholars believe that children…
Descriptors: Speech Impairments, Physical Disabilities, Children, Language Processing
Po-Chun Huang; Ying-Hong Chan; Ching-Yu Yang; Hung-Yuan Chen; Yao-Chung Fan – IEEE Transactions on Learning Technologies, 2024
Question generation (QG) task plays a crucial role in adaptive learning. While significant QG performance advancements are reported, the existing QG studies are still far from practical usage. One point that needs strengthening is to consider the generation of question group, which remains untouched. For forming a question group, intrafactors…
Descriptors: Automation, Test Items, Computer Assisted Testing, Test Construction
Nia Nickerson – ProQuest LLC, 2024
Most of the world's languages include multiple varieties and dialects. Individual ability to successfully alternate between these varieties can be a socio-cultural and academic necessity for many bilingual speakers, including children in the US who alternate between African American English (AAE) and Mainstream American English (MAE). This…
Descriptors: Bilingualism, Language Processing, Brain Hemisphere Functions, Dialects
Alicia Mason – ProQuest LLC, 2024
Theoretical phonology has at its heart the assumption of two separate levels of speech sound representations: one less abstract, phonetic, 'surface' level, and one more abstract, phonological, 'underlying' level. Descriptions of phonological neutralisation processes such as German final devoicing hinge on the mappings between these two levels, as…
Descriptors: German, Phonology, Phonemes, Language Processing
Liunian Li – ProQuest LLC, 2024
To build an Artificial Intelligence system that can assist us in daily lives, the ability to understand the world around us through visual input is essential. Prior studies train visual perception models by defining concept vocabularies and annotate data against the fixed vocabulary. It is hard to define a comprehensive set of everything, and thus…
Descriptors: Artificial Intelligence, Visual Stimuli, Visual Perception, Models
Naz Deniz Atik; Alexander LaTourrette; Sandra R. Waxman – Developmental Science, 2024
To learn the meaning of a new word, or to recognize the meaning of a known one, both children and adults benefit from surrounding words, or the sentential context. Most of the evidence from children is based on their accuracy and efficiency when listening to speech in their familiar native accent: they successfully use the words they know to…
Descriptors: Preschool Children, Speech Communication, Language Processing, Listening
Interaction between Word Processing and Low-Level Visual Representation in Autistic College Students
Nicolás Acuña Luongo; Valeria Arriaza – Mind, Brain, and Education, 2025
Recent studies reported a differential multisensory integration (MSI) in autism spectrum disorder (ASD). Much of the research on MSI differences has focused on how visual stimuli influence speech processing. The present study takes a reverse perspective. We investigated if speech processing can affect the construction of low-level visual…
Descriptors: Visual Perception, Autism Spectrum Disorders, College Students, Multisensory Learning
Hatice Yildiz Durak; Figen Egin; Aytug Onan – European Journal of Education, 2025
Generative artificial intelligence (GenAI) models, such as ChatGPT, Gemini, and BingAI, have become integral to educational sciences, bringing about significant transformations in the education system and the processes of knowledge production. These advancements have facilitated new methods of teaching, learning, and information dissemination.…
Descriptors: Writing (Composition), Discussion, Artificial Intelligence, Natural Language Processing

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