Chung-Ang University Study Validates the Simple View of Reading for Enhancing Second and Foreign Language Learners' Experience

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Aug 18, 2023, 08:39 ET

SEOUL, South Korea, Aug. 18, 2023 /PRNewswire/ -- The simple view of reading (SVR) is a widely accepted theory that attempts to define the skills that contribute to early reading comprehension. It attributes a person's reading comprehension ability to two skills—word recognition (decoding) and language comprehension. However, SVR is known to have some limitations in the context of second as well as foreign languages (SFL). Recent reading research indicates that SVR needs to be expanded upon to include cognitive factors which may impact reading comprehension, such as working memory and inference making, along with metalinguistic skills. This is also necessary in the context of SFL.

Extending the Simple View of Reading in Second and Foreign Language Learning: A Meta-Analytic Structural Equation Modeling Approach

A new study led by Professor Jang Ho Lee of Chung-Ang University along with Professor Hansol Lee of the Korea Military Academy, evaluated SVR in the context of SFL using a statistical approach known as meta-analytic structural equation modeling (MASEM). Their study, published online on 24 July 2023 in Review of Educational Research journal, demonstrates that the primary tenet of SVR holds true in SFL contexts and that it can be adapted to identify reading problems in people reading SFL.

"The SVR model is a time-tested model of reading in the field of first language literacy, and has been used for the development of instructional guidelines of many countries' reading curricula. However, we decided to test the applicability of this model for SFL reading, which has till now been explained by many theories and conflicting ideas," explains Prof. Lee.

The researchers selected 152 prior studies for building the MASEM model, through a database search. Next, the researchers identified 12 variables spanning various SFL constructs, such as comprehension, decoding, cognition, and metalinguistic skills. Further, they used a two-stage modeling approach, known as two-stage structural equation modeling (TSSEM).

They developed four MASEM models, which were variants of the base model, for answering the four research questions in this study. While the base model included variables of reading comprehension, the other three models were expanded to include variables for cognition skills, metalinguistic components, and a combination of both. This helped the researchers to study more complex constructs of SFL reading, compared with the base model.

Their analysis revealed decoding skills and language comprehension skills to be the primary components for effective SFL reading instruction. They identified that early instruction should focus mainly on developing decoding skills and language comprehension skills, while later instruction should focus mainly on developing language comprehension skills. Their findings also underscore the need for including specific instruction on metalinguistic skills in the SFL-SVR framework.

The researchers detail how the extended SVR models can be implemented practically for improving the reading abilities of SFL learners. "The findings that components such as decoding and language comprehension are crucial for SFL reading, can help instructors design a more effective and efficient pedagogical approach. This can ultimately help in promoting SFL learners' reading competence," explains an optimistic Prof. Lee.

This pioneering research could be potentially applied to tackle open research questions in several domains. As Prof. Lee notes, "This is one of the first studies to use a specialized type of meta-analysis for finding answers to the unanswered questions in the field of applied linguistics. Going ahead, researchers can benefit from using this approach to advance the understanding of several issues that involve the complex relationships among multiple variables."

Reference
Title of original paper: Extending the Simple View of Reading in Second and Foreign Language Learning: A Meta-Analytic Structural Equation Modeling Approach
Journal: Review of Educational Research
DOI: https://doi.org/10.3102/00346543231186605

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SOURCE Chung-Ang University