Adults' self-directed learning of an artificial lexicon: The dynamics of neighborhood reorganization

Abstract

Artificial lexicons have previously been used to examine the time course of the learning and recognition of spoken words, the role of segment type in word learning, and the integration of context during spoken word recognition. However, in all of these studies the experimenter determined the frequency and order of the words to be learned. Here we ask whether adult learners choose, either implicitly or explicitly, to listen to novel words in a particular order based on their acoustic similarity. We use a new paradigm for learning an artificial lexicon in which the learner, rather than the experimenter, determines the order and frequency of exposure to items. We analyze both the temporal clustering of subjects' sampling of lexical neighborhoods during training as well as their performance during repeated testing phases (accuracy and reaction time) to determine the time course of learning these neighborhoods. Subjects sampled the high and low density neighborhoods randomly in early learning, and then over-sampled the high density neighborhood until test performance on both neighborhoods reached asymptote. These results provide a new window on the time-course of learning an artificial lexicon and the role that learners’ implicit preferences play in learning highly confusable words.


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