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John N. Williams; Yuyan Xue – Studies in Second Language Acquisition, 2024
Is it possible to acquire a sensitivity to a regularity in language without intending to and without awareness of what it is? In this conceptual replication and extension of an earlier study (Williams, 2005) participants were trained on a semiartificial language in which determiner choice was dependent on noun animacy. Participants who did not…
Descriptors: Language Acquisition, Artificial Languages, Intuition, Nouns
Erin Pacquetet – ProQuest LLC, 2024
This dissertation explores the relationship between language production processes and recorded typing behaviors among native speakers of English writing in their native language. Typing is quite prevalent in modern societies, as its use is becoming increasingly required in professional and personal settings but it remains largely understudied in…
Descriptors: English, Native Language, Writing (Composition), Word Processing
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Sang-Gu Kang – Journal of Pan-Pacific Association of Applied Linguistics, 2024
This paper reports on a young Korean boy's target-like and non-target-like uses of the Korean negation marker "ani" to express various types of negation in Korean, observed approximately between the ages of 2;2 and 2;5. Besides the target-like usage of "ani" as a sentential adverb for a 'no' response, he used "ani" in…
Descriptors: Korean, Morphemes, Toddlers, Language Acquisition
Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
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Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – International Journal of Artificial Intelligence in Education, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
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Muna Barakat; Nesreen A. Salim; Malik Sallam – Open Praxis, 2025
Integration of ChatGPT into higher education requires assessing university educators' perspectives regarding this novel technology. This study aimed to validate a survey instrument specifically tailored to assess ChatGPT usability and acceptability among university educators based on the Technology Acceptance Model (TAM). The survey instrument…
Descriptors: College Faculty, Teacher Attitudes, Artificial Intelligence, Man Machine Systems
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Mathias Benedek; Roger E. Beaty – Journal of Creative Behavior, 2025
The PISA assessment 2022 of creative thinking was a moonshot effort that introduced significant advancements over existing creativity tests, including a broad range of domains (written, visual, social, and scientific), implementation in many languages, and sophisticated scoring methods. PISA 2022 demonstrated the general feasibility of assessing…
Descriptors: Creative Thinking, Creativity, Creativity Tests, Scoring
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Ekaterina Tour; Mark Pegrum; Shem Macdonald – English Australia Journal, 2025
As artificial intelligence (AI), and especially generative AI, are increasingly impacting daily life, it is becoming essential for learners to acquire AI literacy -- the capability to interact with AI at the interface of technology and the target language. Without AI literacy, they may struggle to navigate AI-driven systems and access benefits of…
Descriptors: English Learners, Technology Uses in Education, Educational Strategies, Artificial Intelligence
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Adam B. Lockwood; Joshua Castleberry – Contemporary School Psychology, 2025
Technological Advances in Artificial Intelligence (AI) have Brought forth the Potential for Models to Assist in Academic Writing. However, Concerns Regarding the Accuracy, Reliability, and Impact of AI in Academic Writing have been Raised. This Study Examined the Capabilities of GPT-4, a state-of-the-art AI Language Model, in Writing an American…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Writing (Composition)
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Yushan Kuerban; Solomon Sunday Oyelere; Ismaila Temitayo Sanusi – International Journal of Technology in Education and Science, 2025
Dyslexia is a learning disability that significantly hinders students' abilities to read and comprehend educational materials, posing a substantial challenge within educational environments. This paper introduces an innovative educational system, ReadSmart, that integrates both Augmented Reality (AR) and Generative Artificial Intelligence (GenAI)…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Computer Simulation
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Silvia García-Méndez; Francisco de Arriba-Pérez; María del Carmen Somoza-López – Science & Education, 2025
Transformer architectures contribute to managing long-term dependencies for natural language processing, representing one of the most recent changes in the field. These architectures are the basis of the innovative, cutting-edge large language models (LLMs) that have produced a huge buzz in several fields and industrial sectors, among the ones…
Descriptors: Natural Language Processing, Artificial Intelligence, Literature Reviews, Technology Uses in Education
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Yi Lyu; Azhar Bin Md Adnan; Lijuan Zhang – Education and Information Technologies, 2025
This study presents a comprehensive examination of the applications, challenges, and strategies associated with the integration of natural language processing (NLP) technologies in university teaching. By employing qualitative analyses, including interviews, classroom observations, and document review, the study explores the diverse applications…
Descriptors: Foreign Countries, Natural Language Processing, Technology Integration, Teaching Methods
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Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
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Gal Sasson Lazovsky; Tuval Raz; Yoed N. Kenett – Journal of Creative Behavior, 2025
As artificial intelligence and natural language processing methods rapidly develop, communication plays a pivotal role in every-day interactions. In this theoretical paper, we explore the overlap and commonalities between question-asking and prompt engineering. While seemingly distinct, these processes share a common foundation in essential skills…
Descriptors: Creativity, Questioning Techniques, Inquiry, Artificial Intelligence
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Ola Ghawi-Dakwar; Elinor Saiegh-Haddad – Journal of Speech, Language, and Hearing Research, 2025
Purpose: Word learning requires the creation of phonological and semantic representations and links in long-term memory. Phonological distance of a given word from the spoken language affects children's lexical-phonological representations and processing. The study investigates the role of the phonological distance of Modern Standard Arabic (StA)…
Descriptors: Vocabulary Development, Arabic, Bilingualism, Phonology
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