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Role of prior knowledge in implicit and explicit learning of artificial grammars
journal contribution
posted on 2023-06-08, 21:33 authored by Eleni Ziori, Emmanuel M Pothos, Zoltan DienesZoltan DienesArtificial grammar learning (AGL) performance reflects both implicit and explicit processes and has typically been modeled without incorporating any influence from general world knowledge. Our research provides a systematic investigation of the implicit vs. explicit nature of general knowledge and its interaction with knowledge types investigated by past AGL research (i.e., rule- and similarity-based knowledge). In an AGL experiment, a general knowledge manipulation involved expectations being either congruent or incongruent with training stimulus structure. Inconsistent observations paradoxically led to an advantage in structural knowledge and in the use of general world knowledge in both explicit (conscious) and implicit (unconscious) cases (as assessed by subjective measures). The above findings were obtained under conditions of reduced processing time and impaired executive resources. Key findings from our work are that implicit AGL can clearly be affected by general knowledge, and implicit learning can be enhanced by the violation of expectations.
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Publication status
- Published
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- Published version
Journal
Consciousness and CognitionISSN
1053-8100Publisher
ElsevierExternal DOI
Volume
28Page range
1-16Department affiliated with
- Psychology Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2015-07-10First Compliant Deposit (FCD) Date
2015-07-10Usage metrics
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