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Exploring Reading Strategy Use in Native and L2 Readers

Bibliographic Data

ID11272983
AuthorsDina Feller (0000-0002-1760-3276, Northern Illinois University, corresponding author), Daniel P Feller, Ryan D Kopatich (0000-0002-4133-4280, Northern Illinois University), Iwona Lech (Northern Illinois University), Iwona B Lech (0000-0002-0213-4198, Northern Illinois University), Karyn Higgs (Northern Illinois University)
Year2020
Volume57
Issue7
Pages590-608
Publication date2020-08-08
Open AccessNo
TypeARTICLE
VenueDiscourse Processes (JOURNAL)
Journal identifiersISSN: 0163-853X • E-ISSN: 1532-6950
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/0163853x.2020.1735282
OpenAlexW3011849214
LanguageEN
Citations received2
References cited75

Research comparing the reading strategy use of native and second language (L2) readers has often relied on self-report measures and has, at times, been conducted without measures of reading proficiency. In the present study we used regression and Bayes’ factors to explore how L2 reader status and reading proficiency relate to self-report reading strategy use and the use of situated text processing strategies (i.e., paraphrasing, bridging, and elaboration). Data were collected from a South Central community college district as part of an ongoing study. L2 status did not predict self-reported strategy use, bridging, or elaboration but was associated with increased paraphrasing (in the regression analysis only). Reading proficiency was negatively associated with self-reported use of support strategies but positively predicted the use of all situated processing strategies. Results have important implications for L2 learning and instruction and provide insights into aspects of assessment for L2 readers

Bridging (networking · Elaboration · Language proficiency · Linguistics · Mathematics education · Reading (process · Situated · Computer Science · Educational Strategies and Epistemologies · Psychology · Reading and Literacy Development · Second Language Acquisition and Learning · Artificial Intelligence

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Citations per year0.67
Citation span2023 - 2024 (2)
Highly citedNo

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