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Stefan E. Huber; Kristian Kiili; Steve Nebel; Richard M. Ryan; Michael Sailer; Manuel Ninaus – Educational Psychology Review, 2024
This perspective piece explores the transformative potential and associated challenges of large language models (LLMs) in education and how those challenges might be addressed utilizing playful and game-based learning. While providing many opportunities, the stochastic elements incorporated in how present LLMs process text, requires domain…
Descriptors: Artificial Intelligence, Language Processing, Models, Play
Frank, Stefan L. – Language Learning, 2021
Although computational models can simulate aspects of human sentence processing, research on this topic has remained almost exclusively limited to the single language case. The current review presents an overview of the state of the art in computational cognitive models of sentence processing, and discusses how recent sentence-processing models…
Descriptors: Multilingualism, Language Processing, Computational Linguistics, Psycholinguistics
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
Patience Stevens; David C. Plaut – Grantee Submission, 2022
The morphological structure of complex words impacts how they are processed during visual word recognition. This impact varies over the course of reading acquisition and for different languages and writing systems. Many theories of morphological processing rely on a decomposition mechanism, in which words are decomposed into explicit…
Descriptors: Written Language, Morphology (Languages), Word Recognition, Reading Processes
Stringer, David – Second Language Research, 2021
Westergaard (2021) presents an updated account of the Linguistic Proximity Model and the micro-cue approach to the parser as an acquisition device. The property-by-property view of transfer inherent in this approach contrasts with other influential models that assume that third language (L3) acquisition involves the creation of a full copy of only…
Descriptors: Transfer of Training, Linguistic Theory, Second Language Learning, Multilingualism
González-Bueno, Manuela – Applied Language Learning, 2021
A new technique to teach language grammar is proposed. It consists of the blending of two previously existing techniques--VanPatten's (1996) Processing Instruction (PI) and Adair-Hauck and Donato's (2002) Presentation, Attention, Co-construct, and Extension (PACE) Model. The result is the S-PACE Model, which incorporates the whole-language…
Descriptors: Grammar, Second Language Learning, Second Language Instruction, Teaching Methods
Lieven, Elena; Ferry, Alissa; Theakston, Anna; Twomey, Katherine E. – First Language, 2020
During language acquisition children generalise at multiple layers of granularity. Ambridge argues that abstraction-based accounts suffer from lumping (over-general abstractions) or splitting (over-precise abstractions). Ambridge argues that the only way to overcome this conundrum is in a purely exemplar/analogy-based system in which…
Descriptors: Language Acquisition, Children, Generalization, Abstract Reasoning
Hoeben Mannaert, Lara; Dijkstra, Katinka – International Journal of Behavioral Development, 2021
Over the past decade or so, developments in language comprehension research in the domain of cognitive aging have converged on support for resilience in older adults with regard to situation model updating when reading texts. Several studies have shown that even though age-related declines in language comprehension appear at the level of the…
Descriptors: Young Adults, Older Adults, Language Processing, Resilience (Psychology)
González Alonso, Jorge; Rothman, Jason – Second Language Research, 2021
In this commentary to Westergaard (2021), we focus on two main questions. The first, and most important, is what type of L3 data may be construed as supporting evidence--as opposed to a compatible outcome--for the Linguistic Proximity Model. In this regard, we highlight a number of areas in which it remains difficult to derive testable predictions…
Descriptors: Transfer of Training, Second Language Learning, Native Language, Linguistic Theory
Koring, Loes; Giblin, Iain; Thornton, Rosalind; Crain, Stephen – First Language, 2020
This response argues against the proposal that novel utterances are formed by analogy with stored exemplars that are close in meaning. Strings of words that are similar in meaning or even identical can behave very differently once inserted into different syntactic environments. Furthermore, phrases with similar meanings but different underlying…
Descriptors: Language Acquisition, Figurative Language, Syntax, Phrase Structure
Demuth, Katherine; Johnson, Mark – First Language, 2020
Exemplar-based learning requires: (1) a segmentation procedure for identifying the units of past experiences that a present experience can be compared to, and (2) a similarity function for comparing these past experiences to the present experience. This article argues that for a learner to learn a language these two mechanisms will require…
Descriptors: Comparative Analysis, Language Acquisition, Linguistic Theory, Grammar
Zettersten, Martin; Schonberg, Christina; Lupyan, Gary – First Language, 2020
This article reviews two aspects of human learning: (1) people draw inferences that appear to rely on hierarchical conceptual representations; (2) some categories are much easier to learn than others given the same number of exemplars, and some categories remain difficult despite extensive training. Both of these results are difficult to reconcile…
Descriptors: Models, Language Acquisition, Prediction, Language Processing
McClelland, James L. – First Language, 2020
Humans are sensitive to the properties of individual items, and exemplar models are useful for capturing this sensitivity. I am a proponent of an extension of exemplar-based architectures that I briefly describe. However, exemplar models are very shallow architectures in which it is necessary to stipulate a set of primitive elements that make up…
Descriptors: Models, Language Processing, Artificial Intelligence, Language Usage
Adger, David – First Language, 2020
The syntactic behaviour of human beings cannot be explained by analogical generalization on the basis of concrete exemplars: analogies in surface form are insufficient to account for human grammatical knowledge, because they fail to hold in situations where they should, and fail to extend in situations where they need to. [For Ben Ambridge's…
Descriptors: Syntax, Figurative Language, Models, Generalization
Hartshorne, Joshua K. – First Language, 2020
Ambridge argues that the existence of exemplar models for individual phenomena (words, inflection rules, etc.) suggests the feasibility of a unified, exemplars-everywhere model that eschews abstraction. The argument would be strengthened by a description of such a model. However, none is provided. I show that any attempt to do so would immediately…
Descriptors: Models, Language Acquisition, Language Processing, Bayesian Statistics

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