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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
Claudio-Rafael Vasquez-Martinez; Francisco Flores-Cuevas; Felipe-Anastacio Gonzalez-Gonzalez; Luz-Maria Zuniga-Medina; Graciela-Esperanza Giron-Villacis; Irma-Carolina Gonzalez-Sanchez; Joaquin Torres-Mata – Bulgarian Comparative Education Society, 2024
Language is the basis of human communication and is the most important key to complete mental development and thinking. Therefore, children must learn to communicate using appropriate language. For this to happen, the development of language in the child must be understood as a biological process, complete with internal laws and with marked stages…
Descriptors: Infants, Morphology (Languages), Syntax, Phonology
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
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
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
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
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
Maho Takahashi – ProQuest LLC, 2024
This dissertation features a relative clause island, whose status has been known to differ significantly across languages and extraction types. By conducting a series of acceptability judgment experiments with human participants, as well as measuring token-by-token surprisal values among large language models, I demonstrate the following: First,…
Descriptors: Phrase Structure, Computational Linguistics, Decision Making, Task Analysis
Farrow, Robert – Learning, Media and Technology, 2023
Explicable AI in education (XAIED) has been proposed as a way to improve trust and ethical practice in algorithmic education. Based on a critical review of the literature, this paper argues that XAI should be understood as part of a wider socio-technical turn in AI. The socio-technical perspective indicates that explicability is a relative term.…
Descriptors: Artificial Intelligence, Algorithms, Computer Uses in Education, Language Usage
Cychosz, Margaret; Mahr, Tristan; Munson, Benjamin; Newman, Rochelle; Edwards, Jan R. – Child Development, 2023
To learn language, children must map variable input to categories such as phones and words. How do children process variation and distinguish between variable pronunciations ("shoup" for "soup") versus new words? The unique sensory experience of children with cochlear implants, who learn speech through their device's degraded…
Descriptors: Preschool Children, Child Language, Pronunciation, Assistive Technology
Sello Prince Sekwatlakwatla; Vusumuzi Malele – International Journal of Education and Development using Information and Communication Technology, 2023
The emerging generative artificial intelligence (AI) chatbots, such as Chat Generative Pre-Trained Transformer (ChatGPT), have recently taken different disciplines by surprise. Very few scholarly papers show the collaborative effort by researchers on the impact of generative AI in higher education (HE) and its implication on HE disciplines and…
Descriptors: Artificial Intelligence, Natural Language Processing, Higher Education, Technology Uses in Education
Sang-Gu Kang – Journal of Pan-Pacific Association of Applied Linguistics, 2023
Generative AIs such as Google Bard are known to be equipped with techniques and grammatical principles of human language based on a large corpus of text and code that allow them to generate natural-sounding language, and also identify and correct grammatical errors in human-written texts. Still, they are not perfect language generators, and this…
Descriptors: Artificial Intelligence, Natural Language Processing, Error Correction, Writing (Composition)
Chi Dat Lam – ProQuest LLC, 2023
In everyday life, humans rely on working memory (WM) processes to make sense of relationships between linguistic elements that are not linearly adjacent. For example, to understand the sentence "The dog that the cat chased is cute," we encode the referent "the dog" into WM, maintain and retrieve it after reading the verb…
Descriptors: Short Term Memory, Language Processing, Sentence Structure, Reading Comprehension
Kanan Benjamin Luce – ProQuest LLC, 2023
Previous research has found mixed results for a link between executive function and perspective-taking. One proposed reason for this is that perspective-taking during comprehension tasks may not be internally reliable. This dissertation presents two large individual differences experiments with multiple perspective-taking during comprehension and…
Descriptors: Individual Differences, Perspective Taking, Language Processing, Executive Function
Stephen J. Lupker; Giacomo Spinelli – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
Rastle et al. (2004) reported that true (e.g., walker) and pseudo (e.g., corner) multi-morphemic words prime their stem words more than form controls do (e.g., brothel priming BROTH) in a masked priming lexical decision task. This data pattern has led a number of models to propose that both of the former word types are "decomposed" into…
Descriptors: Models, Morphemes, Priming, Vocabulary