2023
DOI: 10.1111/lang.12569
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Error‐Correction Mechanisms in Language Learning: Modeling Individuals

Abstract: Since its first adoption as a computational model for language learning, evidence has accumulated that Rescorla–Wagner error‐correction learning (Rescorla & Wagner, 1972) captures several aspects of language processing. Whereas previous studies have provided general support for the Rescorla–Wagner rule by using it to explain the behavior of participants across a range of tasks, we focus on testing predictions generated by the model in a controlled natural language learning task and model the data at the le… Show more

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Cited by 5 publications
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