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Breaking it down: a study of morphological awareness in the English reading processes of linguistically diverse middle school students

Morphological awareness (MA) is the knowledge of word structure and capacity to manipulate the meaningful parts of words (Kuo & Anderson, 2006). This study examined derivational MA in the English reading processes of 85 linguistically diverse middle school students in grades six through eight. 56 participants had a native/home language (L1) of Spanish, Portuguese, Chinese, Haitian Creole, or Cape Verdean Creole (CVC) and were acquiring English as a second language (L2). 29 participants were L1 English speakers, which facilitated comparisons between L1 and L2 English readers in how three predictors—MA, word reading, and vocabulary knowledge—related to English reading comprehension. Tests were administered in English to assess word reading, reading comprehension, MA, reading vocabulary, and silent word reading fluency for all 85 participants.

The study a.) Explored the unique contribution of English MA to English reading comprehension; b.) Examined this relationship in light of English word reading and English vocabulary knowledge; c.) Compared linear regression models to examine which factor (or combination of these factors) explained the most variation in English reading comprehension; d.) Looked at differences in the relationships between the reading variables for L2 English readers, based on L1 background; and e.) Explored L1 background as a possible moderator between MA and L2 English reading comprehension; and e.) Observed potential differences in these relationships between L1 and L2 English readers.

All four measures correlated with L2 English reading comprehension for the combined group of L2 English readers, yet MA showed the strongest association. MA was also found to predict L2 English reading comprehension—as did word reading and vocabulary knowledge—when controlling for grade/ time of testing, district, and socio-economic status (SES). Using the same control variables, the bivariate model of MA and English word reading was equal in strength to the model combining MA, word reading, and vocabulary knowledge to predict L2 reading comprehension. Vocabulary knowledge did not add significant predictive value.

Differences by L1 background were seen in correlations and in various regression models predicting L2 English reading comprehension. Controlling for grade/time of testing, district, and SES, MA alone created the best model to explain variance in L2 reading comprehension for Chinese speakers. For Portuguese speakers—using the same controls—the combination of MA, word reading, and vocabulary created the best predictive model for L2 English reading comprehension. The bivariate model of vocabulary and MA and the combined model with all three variables equally predicted English reading comprehension for Spanish speakers. No models effectively predicted English reading comprehension for Haitian Creole speakers. The model combining all three predictors explained the most variance in L2 reading comprehension. Additionally, L1 did not moderate the relationship of MA to L2 English reading comprehension.

For L1 speakers of English, MA uniquely predicted English reading comprehension—as did word reading, and vocabulary—when controlling for grade/time of testing, district, and SES. However, the best predictor of L1 English reading comprehension was the combined contribution of MA, word reading, and vocabulary knowledge. L1 and L2 English readers differed in the correlations between variables and in how well the various regression models explained variance in English reading comprehension. The controls of grade/time of testing and SES were significant as predictors in models of L1 English reading comprehension. Z- tests did not reveal significant differences when comparing the correlation coefficients of independent variables in the regression models. Implications for instruction and future research are presented.

Identiferoai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/38240
Date29 September 2019
CreatorsLaBelle, Melissa Tobey
ContributorsO' Connor, Catherine, Leider, Christine M.
Source SetsBoston University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

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