Children improve at word learning during the 2nd year of life—sometimes dramatically. This fact has suggested a change in mechanism, from associative learning to a more referential form of learning. This article presents an associative exemplar-based model that accounts for the improvement without a change in mechanism. It provides a unified account of children's growing abilities to (a) learn a new word given only 1 or a few training trials (“fast mapping”); (b) acquire words that differ only slightly in phonological (...) form; (c) generalize word meanings preferentially along particular dimensions, such as object shape (the “shape bias”); and (d) learn 2nd labels for already-named objects, despite a persisting resistance to doing so (“mutual exclusivity”). The model explains these improvements in terms of increased attention to relevant aspects of form and meaning, which reduces memory interference. The interaction of associations and reference in word learning is discussed. (shrink)

Symbols enable people to organize and communicate about the world. However, the ways in which symbolic knowledge is learned and then represented in the mind are poorly understood. We present a formal analysis of symbolic learning—in particular, word learning—in terms of prediction and cue competition, and we consider two possible ways in which symbols might be learned: by learning to predict a label from the features of objects and events in the world, and by learning to predict features from a (...) label. This analysis predicts significant differences in symbolic learning depending on the sequencing of objects and labels. We report a computational simulation and two human experiments that confirm these differences, revealing the existence of Feature-Label-Ordering effects in learning. Discrimination learning is facilitated when objects predict labels, but not when labels predict objects. Our results and analysis suggest that the semantic categories people use to understand and communicate about the world can only be learned if labels are predicted from objects. We discuss the implications of this for our understanding of the nature of language and symbolic thought, and in particular, for theories of reference. (shrink)

Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed when, during the course of these dynamic recognition processes, learned representations are formed and updated. If learned representations are formed and updated while recognition is ongoing, the result of learning (...) may incorporate spurious, partial information. For example, during word recognition, words take time to be identified, and competing words are often active in parallel. If learning proceeds before this competition resolves, representations may be influenced by the preliminary activations present at the time of learning. In three experiments using word learning as a model domain, we provide evidence that learning reflects the ongoing dynamics of auditory and visual processing during a learning event. These results show that learning can occur before stimulus recognition processes are complete; learning does not wait for ongoing perceptual processing to complete. (shrink)