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Adults Use Distributional Statistics for Word Learning in a Conservative Way
Aussems,Suzanne Vogt,Paul
Aussems,Suzanne
Vogt,Paul
Abstract
This study examined how much adults rely on cross-situational information in word learning by comparing their gaze behavior in a word learning task with models of four learning strategies. We manipulated the input type of situations (consecutive vs. interleaved) and the co-occurrence frequencies between words and objects so that adult learners could infer correct word-object mappings based on cross-situational information. There are two key findings. First, an exposure-by-exposure analysis of gaze behavior during the word learning procedure revealed that most participants collected sufficient cross-situational information before they developed a preference for one particular word-object mapping, with consecutive as well as interleaved situations. Second, a classification approach in which individual gaze behavior was attributed to different word learning strategies showed that participants relied mostly on a Conservative cross-situational learning (XSL) strategy, compared to Associative XSL, Propose-but-Verify, and Random strategies. Adults relied on Conservative XSL when presented with consecutive and interleaved situations, but they shifted towards Associative XSL when presented with interleaved situations.
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2020
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FINAL_VERSION.pdf
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Aussems, S & Vogt, P 2020, 'Adults Use Distributional Statistics for Word Learning in a Conservative Way', IEEE Transactions on Cognitive and Developmental Systems, vol. 12, no. 2, pp. 232-242. https://doi.org/10.1109/TCDS.2018.2870161
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info:eu-repo/semantics/openAccess