Taking Development Seriously: Modeling the Interactions in the Emergence of Different Word Learning Biases

Abstract

Development is about change over time. Computational models have provided insights into the developmental changes seen in different cognitive phenomena, including within the domain of word learning. The present paper uses a computational model to investigate the interdependencies between the emergence of different word learning biases. This model allows investigation of how the emergence of the shape bias influences novel noun generalization to two other types of items. The results suggest that the emerging shape bias for solids can either strengthen or weaken other types of biases depending on the strength of the cues to solidity or non-solidity; further, these results make predictions about children’s biased word learning over time.


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