Stella, Marianna and Engelhardt, Paul E. (2022) Use of parsing heuristics in the comprehension of passive sentences: Evidence from dyslexia and individual differences. Brain Sciences, 12 (2). ISSN 2076-3425
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Abstract
This study examined the comprehension of passive sentences in order to investigate whether in-dividuals with dyslexia rely on parsing heuristics in language comprehension to a greater extent than non-dyslexic readers. One hundred adults (50 dyslexics and 50 controls) read active and passive sentences, and we also manipulated semantic plausibility. Eye movements were moni-tored, while participants read each sentence, and afterwards, participants answered a compre-hension question. We also assessed verbal intelligence and working memory in all participants. Results showed dyslexia status interacted with sentence structure and plausibility, such that par-ticipants with dyslexia showed significantly more comprehension errors with passive and im-plausible sentence. With respect to verbal intelligence and working memory, we found that in-dividuals with lower verbal intelligence were overall more likely to make comprehension errors, and individuals with lower working memory showed particular difficulties with passive and implausible sentences. For reading times, we found that individuals with dyslexia were overall slower readers. These findings suggest that (1) individuals with dyslexia do rely on heuristics to a greater extent than do non-dyslexic individuals, and (2) individual differences variables (e.g., verbal intelligence and working memory) are also related to the use of parsing heuristics. For the latter, lower ability individuals tended to be more consistent with heuristic processing (i.e., good-enough representations).
Item Type: | Article |
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Faculty \ School: | Faculty of Social Sciences > School of Psychology |
Depositing User: | LivePure Connector |
Date Deposited: | 01 Feb 2022 11:30 |
Last Modified: | 23 Oct 2022 03:30 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/83249 |
DOI: | 10.3390/brainsci12020209 |
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