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Chi-hsin Chen; Yayun Zhang; Chen Yu – Cognitive Science, 2025
Learning the meaning of a verb is challenging because learners need to resolve two types of ambiguity: (1) word-referent mapping--finding the correct referent event of a verb, and (2) word-meaning mapping--inferring the correct meaning of the verb from the referent event (e.g., whether the meaning of an action word is TURNING or TWISTING). The…
Descriptors: Verbs, Ambiguity (Semantics), Adult Students, Linguistic Input
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Perkins, Laurel; Feldman, Naomi H.; Lidz, Jeffrey – Cognitive Science, 2022
Learning in any domain depends on how the data for learning are represented. In the domain of language acquisition, children's representations of the speech they hear determine what generalizations they can draw about their target grammar. But these input representations change over development as a function of children's developing linguistic…
Descriptors: Persuasive Discourse, Language Acquisition, Form Classes (Languages), Verbs
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Jiang, Hang; Frank, Michael C.; Kulkarni, Vivek; Fourtassi, Abdellah – Cognitive Science, 2022
The linguistic input children receive across early childhood plays a crucial role in shaping their knowledge about the world. To study this input, researchers have begun applying distributional semantic models to large corpora of child-directed speech, extracting various patterns of word use/co-occurrence. Previous work using these models has not…
Descriptors: Caregivers, Caregiver Child Relationship, Linguistic Input, Semantics
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Wang, Wentao; Vong, Wai Keen; Kim, Najoung; Lake, Brenden M. – Cognitive Science, 2023
Neural network models have recently made striking progress in natural language processing, but they are typically trained on orders of magnitude more language input than children receive. What can these neural networks, which are primarily distributional learners, learn from a naturalistic subset of a single child's experience? We examine this…
Descriptors: Brain Hemisphere Functions, Linguistic Input, Longitudinal Studies, Self Concept
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Oliveira, Cátia M.; Henderson, Lisa M.; Hayiou-Thomas, Marianna E. – Cognitive Science, 2023
The ability to extract patterns from sensory input across time and space is thought to underlie the development and acquisition of language and literacy skills, particularly the subdomains marked by the learning of probabilistic knowledge. Thus, impairments in procedural learning are hypothesized to underlie neurodevelopmental disorders, such as…
Descriptors: Linguistic Input, Task Analysis, Reaction Time, Language Impairments
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Sakine Çabuk-Balli; Jekaterina Mazara; Aylin C. Küntay; Birgit Hellwig; Barbara B. Pfeiler; Paul Widmer; Sabine Stoll – Cognitive Science, 2025
Negation is a cornerstone of human language and one of the few universals found in all languages. Without negation, neither categorization nor efficient communication would be possible. Languages, however, differ remarkably in how they express negation. It is yet widely unknown how the way negation is marked influences the acquisition process of…
Descriptors: Morphemes, Native Language, Language Acquisition, Infants
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Ger, Ebru; You, Guanghao; Küntay, Aylin C.; Göksun, Tilbe; Stoll, Sabine; Daum, Moritz M. – Cognitive Science, 2022
Becoming productive with grammatical categories is a gradual process in children's language development. Here, we investigated this transition process by focusing on Turkish causatives. Previous research examining spontaneous and elicited production of Turkish causatives with familiar verbs attested the onset and early stages of productivity at…
Descriptors: Turkish, Morphology (Languages), Longitudinal Studies, Computational Linguistics