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  1. Goldilocks Forgetting in Cross-Situational Learning.Paul Ibbotson, Diana G. López & Alan J. McKane - 2018 - Frontiers in Psychology 9:387015.
    Given that there is referential uncertainty (noise) when learning words, to what extent can forgetting filter some of that noise out, and be an aid to learning? Using a Cross Situational Learning model we find a U-shaped function of errors indicative of a “Goldilocks” zone of forgetting: an optimum store-loss ratio that is neither too aggressive nor too weak, but just the right amount to produce better learning outcomes. Forgetting acts as a high-pass filter that actively deletes (part of) the (...)
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  • Does Variability Across Events Affect Verb Learning in English, Mandarin, and Korean?Jane B. Childers, Jae H. Paik, Melissa Flores, Gabrielle Lai & Megan Dolan - 2017 - Cognitive Science 41 (S4):808-830.
    Extending new verbs is important in becoming a productive speaker of a language. Prior results show children have difficulty extending verbs when they have seen events with varied agents. This study further examines the impact of variability on verb learning and asks whether variability interacts with event complexity or differs by language. Children in the United States, China, Korea, and Singapore learned verbs linked to simple and complex events. Sets of events included one or three agents, and children were asked (...)
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  • Gavagai Is as Gavagai Does: Learning Nouns and Verbs From Cross‐Situational Statistics.Padraic Monaghan, Karen Mattock, Robert A. I. Davies & Alastair C. Smith - 2015 - Cognitive Science 39 (5):1099-1112.
    Learning to map words onto their referents is difficult, because there are multiple possibilities for forming these mappings. Cross-situational learning studies have shown that word-object mappings can be learned across multiple situations, as can verbs when presented in a syntactic context. However, these previous studies have presented either nouns or verbs in ambiguous contexts and thus bypass much of the complexity of multiple grammatical categories in speech. We show that noun word learning in adults is robust when objects are moving, (...)
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  • A Computational Model for the Item‐Based Induction of Construction Networks.Judith Gaspers & Philipp Cimiano - 2014 - Cognitive Science 38 (3):439-488.
    According to usage‐based approaches to language acquisition, linguistic knowledge is represented in the form of constructions—form‐meaning pairings—at multiple levels of abstraction and complexity. The emergence of syntactic knowledge is assumed to be a result of the gradual abstraction of lexically specific and item‐based linguistic knowledge. In this article, we explore how the gradual emergence of a network consisting of constructions at varying degrees of complexity can be modeled computationally. Linguistic knowledge is learned by observing natural language utterances in an ambiguous (...)
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  • Statistical Learning of Language: A Meta‐Analysis Into 25 Years of Research.Erin S. Isbilen & Morten H. Christiansen - 2022 - Cognitive Science 46 (9):e13198.
    Cognitive Science, Volume 46, Issue 9, September 2022.
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  • Cross‐situational Learning From Ambiguous Egocentric Input Is a Continuous Process: Evidence Using the Human Simulation Paradigm.Yayun Zhang, Daniel Yurovsky & Chen Yu - 2021 - Cognitive Science 45 (7):e13010.
    Recent laboratory experiments have shown that both infant and adult learners can acquire word‐referent mappings using cross‐situational statistics. The vast majority of the work on this topic has used unfamiliar objects presented on neutral backgrounds as the visual contexts for word learning. However, these laboratory contexts are much different than the real‐world contexts in which learning occurs. Thus, the feasibility of generalizing cross‐situational learning beyond the laboratory is in question. Adapting the Human Simulation Paradigm, we conducted a series of experiments (...)
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  • A Single Paradigm for Implicit and Statistical Learning.Padraic Monaghan, Christine Schoetensack & Patrick Rebuschat - 2019 - Topics in Cognitive Science 11 (3):536-554.
    This article focuses on the implicit statistical learning of words and syntax. Monaghan, Schoetensack and Rebuschat introduce a novel paradigm that combines theoretical and methodological insights from the two research traditions, implicit learning and statistical learning. Their cross‐situational learning paradigm has been used in the statistical learning literature, while their measures of awareness have widely been used in implicit learning research. They illustrate how the two literatures can be conjoined in a single paradigm to explore implicit statistical learning.
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  • Studying the Real-Time Interpretation of Novel Noun and Verb Meanings in Young Children.Alex de Carvalho, Mireille Babineau, John C. Trueswell, Sandra R. Waxman & Anne Christophe - 2019 - Frontiers in Psychology 10.
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  • Using Verb Extension to Gauge Children’s Verb Meaning Construals: The Case of Chinese.Weiyi Ma, Roberta Michnick Golinkoff, Lulu Song & Kathy Hirsh-Pasek - 2021 - Frontiers in Psychology 11:572198.
    Verb extension is a crucial gauge of the acquisition of verb meaning. In English, studies suggest that young children show conservative extension. An important test of whether an early conservative extension is a general phenomenon or a function of the input language is made possible by Chinese, a language in which verbs are more frequent and acquired earlier. This study tested whether 3-year-old Chinese children extended a group of familiar verbs that specify various ways tocarryobjects. Shown videos that portrayed typical, (...)
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  • What Children with Developmental Language Disorder Teach Us About Cross‐Situational Word Learning.Karla K. McGregor, Erin Smolak, Michelle Jones, Jacob Oleson, Nichole Eden, Timothy Arbisi-Kelm & Ronald Pomper - 2022 - Cognitive Science 46 (2):e13094.
    Children with developmental language disorder (DLD) served as a test case for determining the role of extant vocabulary knowledge, endogenous attention, and phonological working memory abilities in cross-situational word learning. First-graders (Mage = 7 years; 3 months), 44 with typical development (TD) and 28 with DLD, completed a cross-situational word-learning task comprised six cycles, followed by retention tests and independent assessments of attention, memory, and vocabulary. Children with DLD scored lower than those with TD on all measures of learning and (...)
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  • Learning vocabulary and grammar from cross-situational statistics.Patrick Rebuschat, Padraic Monaghan & Christine Schoetensack - 2021 - Cognition 206 (C):104475.
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  • Retrieval Dynamics and Retention in Cross‐Situational Statistical Word Learning.Haley A. Vlach & Catherine M. Sandhofer - 2014 - Cognitive Science 38 (4):757-774.
    Previous research on cross-situational word learning has demonstrated that learners are able to reduce ambiguity in mapping words to referents by tracking co-occurrence probabilities across learning events. In the current experiments, we examined whether learners are able to retain mappings over time. The results revealed that learners are able to retain mappings for up to 1 week later. However, there were interactions between the amount of retention and the different learning conditions. Interestingly, the strongest retention was associated with a learning (...)
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  • The Role of Feedback in the Statistical Learning of Language‐Like Regularities.Felicity F. Frinsel, Fabio Trecca & Morten H. Christiansen - 2024 - Cognitive Science 48 (3):e13419.
    In language learning, learners engage with their environment, incorporating cues from different sources. However, in lab‐based experiments, using artificial languages, many of the cues and features that are part of real‐world language learning are stripped away. In three experiments, we investigated the role of positive, negative, and mixed feedback on the gradual learning of language‐like statistical regularities within an active guessing game paradigm. In Experiment 1, participants received deterministic feedback (100%), whereas probabilistic feedback (i.e., 75% or 50%) was introduced in (...)
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  • When Meaning Is Not Enough: Distributional and Semantic Cues to Word Categorization in Child Directed Speech.Feijoo Sara, Muñoz Carmen, Amadó Anna & Serrat Elisabet - 2017 - Frontiers in Psychology 8.
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  • Learning Object Names at Different Hierarchical Levels Using Cross‐Situational Statistics.Chen Chi-Hsin, Zhang Yayun & Yu Chen - 2018 - Cognitive Science:591-605.
    Objects in the world usually have names at different hierarchical levels (e.g., beagle, dog, animal). This research investigates adults' ability to use cross‐situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use co‐occurrence information to learn hierarchical labels in contexts where the labels for individual objects and labels for categories were presented in completely separated blocks, in interleaved blocks, or mixed in the same trial. Temporal presentation schedules significantly affected (...)
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