Theory-Based Correlations and Their Role in Children's Concepts

Barrett, Susan E.; Abdi, Hervé; Murphy, Gregory L.; Gallagher, Jeanette McCarthy

doi:10.2307/1131458

Cited by 69 publications

(35 citation statements)

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“…Research in this area points to complex interactions between linguistic and non-linguistic input while children learn word meaning (e.g., Barrett, Abdi, Murphy, & Gallagher, 1993;Gelman, 1988;Jones & Smith, 1993). Because of the simplifications in the way the network was trained, it is not appropriate to use it to simulate developmental data.…”

Section: Network Architecturementioning

confidence: 99%

An Attractor Model of Lexical Conceptual Processing: Simulating Semantic Priming

1999

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An attractor network was trained to compute from word form to semantic representations that were based on subject-generated features. The model was driven largely by higher-order semantic structure. The network simulated two recent experiments that employed items included in its training set (McRae and Boisvert, 1998). In Simulation 1, short stimulus onset asynchrony priming was demonstrated for semantically similar items. Simulation 2 reproduced subtle effects obtained by varying degree of similarity. Two predictions from the model were then tested on human subjects. In Simulation 3 and Experiment 1, the items from Simulation 1 were reversed, and both the network and subjects showed minimally different priming effects in the two directions. In Experiment 2, consistent with attractor networks but contrary to a key aspect of hierarchical spreading activation accounts priming was determined by featural similarity rather than shared superordinate category. It is concluded that semantic-similarity priming is due to featural overlap that is a natural consequence of distributed representations of word meaning.

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Section: Network Architecturementioning

confidence: 99%

An Attractor Model of Lexical Conceptual Processing: Simulating Semantic Priming

1999

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“…Thus some researchers have suggested that children's naive theories might be generated by domain-specific modules (Leslie, 1994; Scholl & Leslie, 1999) or innate concepts in core domains (Carey & Spelke, 1994; Keil, 1995), while other NAÏVE THEORIES, AMBIGUOUS EVIDENCE Page 4 researchers have focused on children's ability to learn causal relations from statistical evidence (Gopnik et al, 2004;Gopnik, Sobel, Schulz, & Glymour, 2001;Schulz & Gopnik, 2004; Shultz & Mendelson, 1975; Siegler & Liebert, 1975; Sobel, Tenenbaum, & Gopnik, 2004; Watson & Ramey, 1972). Although some research on the development of scientific reasoning has emphasized the importance of integrating domain-specific knowledge with domain-general strategies (Barrett, Abdi, Murphy, & Gallagher, 1993; Klahr & Dunbar, 1988; Koslowski, 1996; Koslowski, Okagaki, Lorenz, & Umbach, 1989; Pazzani, 1991; Penner & Klahr, 1996; Schauble, 1990), those studies have focused primarily on adolescents and adults. Surprisingly little research has looked at how prior theories and evidence interact in young children's causal learning.…”

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confidence: 99%

Can being scared make your tummy ache? Naive theories, ambiguous evidence and preschoolers’ causal inferences

Schulz¹,

Bonawitz²,

Griffiths³

2018

Preprint

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Causal learning requires integrating constraints provided by domain-specific theories with domain-general statistical learning. In order to investigate the interaction between these factors, preschoolers were presented with stories pitting their existing theories against statistical evidence. Each child heard two stories in which two candidate causes co-occurred with an effect. Evidence was presented in the form: AB àE, AC à E, AD à E, etc. In one story, all variables came from the same domain; in the other, the recurring candidate cause, A, came from a different domain (A was a psychological cause of a biological effect). After receiving this statistical evidence, children were asked to identify the cause of the effect on a new trial. Consistent with the predictions of a Bayesian model, all children were more likely to identify A as the cause within domains than across domains. While three-and-half-year-olds learned only from the withindomain evidence, four-and five-year-olds learned from the cross-domain evidence and were able to transfer their new expectations about psychosomatic causality to a novel task.KEYWORDS: domain-general and domain-specific causal learning, Bayesian models, naïve theories, ambiguous evidence, psychosomatic causes NAÏVE THEORIES, AMBIGUOUS EVIDENCE Page 3Can being scared make your tummy ache? Naive theories, ambiguous evidence and preschoolers' causal inferences By the time children are five years old, they understand causal relationships in a variety of domains (Flavell, Green, & Flavell, 1995;Gelman & Wellman, 1991;Gopnik & Meltzoff, 1997;Inagaki & Hatano, 1993;Kalish, 1996; Perner, 1991; Shultz, 1982; Spelke, Breinlinger, Macomber, & Jacobson, 1992). Many researchers have suggested that children's causal knowledge can be best characterized as a set of naive theories:abstract, coherent representations of causal structure that support prediction, intervention, explanation, and counterfactual claims (Carey, 1985;Harris, German, & Mills, 1996;Hickling & Wellman, 2001;Gopnik, 1988;Gopnik & Meltzoff, 1997;Keil, 1989; Perner, 1991;Sobel, 2004; Wellman, 1990; Wellman, Hickling, & Schult, 1997). The view that children's causal representations resemble scientific theories (the theory theory) suggests both that patterns of evidence should affect children's causal commitments and that children's causal commitments should affect their interpretation of evidence. Indeed, this dynamic relationship between domain-appropriate causal beliefs and evidence has been taken as a defining feature of theories (e.g., Gopnik & Meltzoff, 1997).However, despite the expectation that theory and evidence should interact, developmental psychologists have been largely divided between accounts of causal reasoning emphasizing either domain-specific causal knowledge or domain-general learning from data. Thus some researchers have suggested that children's naive theories might be generated by domain-specific modules (Leslie, 1994; Scholl & Leslie, 1999) or innate concepts in core domains (Carey & Spelke, 1...

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“…This possibility is especially likely in situations where children can interact with the materials in ways that do not require the desired encoding (Uttal, O'Doherty, Newland, Hand, & DeLoache, 2009). Findings from numerous domains indicate that learners often fail to encode relevant dimensions, that inadequate encoding impairs learning, and that instructions that improve encoding of key features or relations improve learning (Alibali, 1999;Barrett, Abdi, Murphy, & Gallagher, 1993;Blaxton, 1989;Brown, Kane, & Echols, 1986;Chi, 1978;McCloskey & Kaiser, 1984;Ornstein et al, 1998;Siegler, 1976;Siegler & Chen, 1998;Staszewski, 1988). Thus, the cognitive alignment framework posits that there is a need, even with the best designed learning materials, for activities that direct learners' behaviors in ways that promote the encoding of the features relevant to the desired mental representation.…”

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confidence: 99%

Learning from number board games: You learn what you encode.

Laski¹,

Siegler²

2014

Developmental Psychology

125

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We tested the hypothesis that encoding the numerical-spatial relations in a number board game is a key process in promoting learning from playing such games. Experiment 1 used a microgenetic design to examine the effects on learning of the type of counting procedure that children use. As predicted, having kindergartners count-on from their current number on the board while playing a 0 -100 number board game facilitated their encoding of the numerical-spatial relations on the game board and improved their number line estimates, numeral identification, and count-on skill. Playing the same game using the standard count-from-1 procedure led to considerably less learning. Experiment 2 demonstrated that comparable improvement in number line estimation does not occur with practice encoding the numerals 1-100 outside of the context of a number board game. The general importance of aligning learning activities and physical materials with desired mental representations is discussed.

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Theory-Based Correlations and Their Role in Children's Concepts

Cited by 69 publications

References 0 publications

An Attractor Model of Lexical Conceptual Processing: Simulating Semantic Priming

An Attractor Model of Lexical Conceptual Processing: Simulating Semantic Priming

Can being scared make your tummy ache? Naive theories, ambiguous evidence and preschoolers’ causal inferences

Learning from number board games: You learn what you encode.

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