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Feature-focusing constraints on implicit learning of function word and meaning associations

Published online by Cambridge University Press:  25 March 2020

Theresa Pham Open the ORCID record for Theresa Pham [Opens in a new window] ,
Joel Hosung Kang ,
Alisha Johnson  and
Lisa M. D. Archibald
Theresa Pham*
Affiliation:
University of Western Ontario
Joel Hosung Kang
Affiliation:
University of Western Ontario
Alisha Johnson
Affiliation:
University of Western Ontario
Lisa M. D. Archibald
Affiliation:
University of Western Ontario
*
*Corresponding author. Email: [email protected]
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Abstract

Recent research has begun to investigate implicit learning at the level of meaning. The general consensus is that implicitly linking a word with a meaning is constrained by existing linguistic knowledge. However, another factor to consider is the extent to which attention is drawn to the relevant meanings in implicit learning paradigms. We manipulated the presence of cue saliency during implicit rule learning for a grammatical form (i.e., articles) linked to meaning (i.e., animacy vs. varying notions of size). In a series of experiments, participants learned four novel words but did not know that article usage also depended on a hidden rule, creating an opportunity for implicit rule learning. We found implicit learning through the use of a highly salient meaning (Experiment 1) or if image size was made salient by being explicitly cued (Experiment 3), but not in a low salient paradigm for intrinsic object size (Experiment 2). The findings suggest that implicit learning of semantic information might not be as constrained as previously argued. Instead, implicit learning might be additionally influenced by feature-focusing cues that make the meaning contrasts more salient and thereby more readily available to learning.

Keywords

attentional cuescue saliencyform–meaning connectionsimplicit learningsemantic association
Type
Original Article
Information
Applied Psycholinguistics , Volume 41 , Issue 2 , March 2020 , pp. 401 - 426
Copyright
© Cambridge University Press 2020

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