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Simple view of second language reading: A meta-analytic structural equation modeling approach
The present study aimed to systemically summarize the structural relationships among correlated components of second language (L2) reading comprehension to investigate the extent to which the two major components - language comprehension abilities and decoding skills - could account for reading comp...
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Published in: | Scientific studies of reading 2022-11, Vol.26 (6), p.585-603 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The present study aimed to systemically summarize the structural relationships among correlated components of second language (L2) reading comprehension to investigate the extent to which the two major components - language comprehension abilities and decoding skills - could account for reading comprehension in L2 contexts in accordance with the model of Simple View of Reading.
We used a meta-analytic structural equation modeling. This study included 81 samples (from 67 studies) including 10,526 participants, and the collected dataset successfully fitted the proposed model of Simple View of L2 Reading.
L2 comprehension abilities and L2 decoding skills accounted for over 60% of the variation in L2 reading comprehension, with the former having a larger contribution. Considering age and L2 proficiency as moderator variables, it was revealed that L2 decoding skills played less important roles for more proficient and older learners, whereas L2 comprehension abilities maintained their importance across different ages and L2 proficiency levels. The moderators related to language differences between learners' first language and L2 did not show significant moderating effects.
The study presented acceptable model fit indices for its models. Future studies can incorporate more pooled correlation coefficients and variables to investigate an effective instruction for L2 reading. |
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ISSN: | 1088-8438 1532-799X |
DOI: | 10.1080/10888438.2022.2087526 |