How young children integrate information sources to infer the meaning of words

Bohn, Manuel; Tessler, Michael Henry; Merrick, Megan; Frank, Michael C.

doi:10.31234/osf.io/2wgfb

Cited by 6 publications

(16 citation statements)

References 51 publications

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“…Understanding how these different strategies are flexibly used in verb learning is an important area for future research (c.f. Bohn, Tessler, Merrick, & Frank, 2021).…”

Section: Small Effect Sizementioning

confidence: 99%

Quantifying the syntactic bootstrapping effect in verb learning: A meta‐analytic synthesis

Cao

Lewis

2021

Developmental Science

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How do children infer the meaning of a novel verb? One prominent proposal is that children rely on syntactic information in the linguistic context, a phenomenon known as "syntactic bootstrapping" . For example, given the sentence "The bunny is gorping the duck," a child could use knowledge of English syntactic roles to infer that "gorping" refers to an action where the bunny is acting in some way on a duck. Here, we examine the strength of the syntactic bootstrapping effect, its developmental trajectory and generalizability using meta-analytic methods. Across 60 experiments in the literature (N = 849 participants), we find a reliable syntactic bootstrapping effect (d = .24). Yet, despite its theoretical prominence, the syntactic bootstrapping effect is relatively small, comparable in size to cross-situational learning and sound symbolism, but smaller than mutual-exclusivity and gaze-following. Further, we find that the effect does not strengthen over development, and is present only for studies that use transitive sentences. An examination of a range of methodological factors suggests that the effect is not strongly influenced by methodological implementation. In the General Discussion, we consider implications of our findings for theories of verb learning and make recommendations for future research.

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“…Understanding how these different strategies are flexibly used in verb learning is an important area for future research (c.f. Bohn, Tessler, Merrick, & Frank, 2021).…”

Section: Small Effect Sizementioning

confidence: 99%

Quantifying the syntactic bootstrapping effect in verb learning: A meta‐analytic synthesis

Cao

Lewis

2021

Developmental Science

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“…We assumed that children would take the novel word to refer to the novel object. In line with previous work (Bohn et al, 2021;Grassmann, Schulze, & Tomasello, 2015;Lewis, Cristiano, Lake, Kwan, & Frank, 2020) we assumed this inference MODELING INDIVIDUAL DIFFERENCES IN DEVELOPMENTAL PRAGMATICS 10 would be modulated by children's lexical knowledge of the familiar object. Children received 16 trials, each with a new pair of novel and familiar objects.…”

Section: Modeling Individual Differences In Developmental Pragmaticsmentioning

confidence: 62%

“…Recent work using RSA models has begun to address this issue. For example, Bohn, Tessler, Merrick, and Frank (2021) studied young children's information integration during pragmatic word learning (see also Bohn, Tessler, Merrick, & Frank, 2022) These prior studies only explained and predicted behavior on an aggregate level, however. The models were assessed following the assumption that the "average person" behaves like the prototypical agent whose cognitive processes are being simulated by the model (Estes & Todd Maddox, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…In the present study, we address this issue in the domain of pragmatic word learning, using RSA models to predict individual differences between children. Our study builds on Bohn et al (2021) and measures how children integrate different information sources. We focused on how children's semantic knowledge interacts with their expectations about informative communication and sensitivity to common ground.…”

Section: Introductionmentioning

confidence: 99%

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Modeling individual differences in children’s information integration during pragmatic word learning

Bohn¹,

Schulze²,

Schmidt³

et al. 2022

Preprint

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Pragmatics is foundational to language use and learning. Computational cognitive models have been successfully used to predict pragmatic phenomena in adults and children -- on an aggregate level. It is unclear if they can be used to predict behavior on an individual level. We address this question in children (N = 60, 3- to 5-year-olds), taking advantage of recent work on pragmatic cue integration. In Part 1, we use data from four independent tasks to estimate child-specific sensitivity parameters to three information sources: semantic knowledge, expectations about speaker informativeness, and sensitivity to common ground. In Part 2, we use these parameters to generate participant-specific trial-by-trial predictions for a new task that jointly manipulated all three information sources. The model accurately predicted children’s behavior in the majority of trials. This work advances a substantive theory of individual differences in which the primary locus of developmental variation is sensitivity to individual information sources.

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“…More recently, it has been used to predict how adults and children integrate different information sources to make inferences about what a speaker is referring to [54]. In one study, Bohn and colleagues [55] measured children's developing sensitivity to different information sources, for example, their linguistic knowledge or their sensitivity to common ground. They then used an RSA-type model to predict what should happen when people are confronted with multiple information sources at once.…”

Section: Computational Models Of Linguistic Communication In Humansmentioning

confidence: 99%

Great ape communication as contextual social inference: a computational modeling perspective

Bohn¹,

Liebal²,

Tessler³

2021

Preprint

Self Cite

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Human communication has been described as a contextual social inference process. Research into great ape communication has been inspired by this view to look for the evolutionary roots of the social, cognitive, and interactional processes involved in human communication. This approach has been highly productive, yet it is often compromised by a too-narrow focus on how great apes use and understand individual signals. In this paper, we introduce a computational model that formalizes great ape communication as a multi-faceted social inference process that relies on information contained in the signal, the relationship between communicative partners, and the social context. This model makes accurate qualitative and quantitative predictions about real-world communicative interactions between semi-wild-living chimpanzees. When enriched with a pragmatic reasoning process, the model explains repeatedly reported differences between humans and great apes in the interpretation of ambiguous signals (e.g. pointing gestures). This approach has direct implications for observational and experimental studies of great ape communication and provides a new tool for theorizing about the evolution of uniquely human communication.

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How young children integrate information sources to infer the meaning of words

Cited by 6 publications

References 51 publications

Quantifying the syntactic bootstrapping effect in verb learning: A meta‐analytic synthesis

Quantifying the syntactic bootstrapping effect in verb learning: A meta‐analytic synthesis

Modeling individual differences in children’s information integration during pragmatic word learning

Great ape communication as contextual social inference: a computational modeling perspective

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