Abstract
This study aims to examine the relationship between reading comprehension and lexical and grammatical knowledge among English as a foreign language students by using an Artificial Neural Network (ANN). There were 825 test takers administered both a second-language reading test and a set of psychometrically validated grammar and vocabulary tests. Next, their reading, grammar, and vocabulary abilities were estimated by the Rasch model. A multilayer ANN was used to classify low- and high-ability readers based on their grammar and vocabulary measures. ANN accurately classified approximately 78% of readers with reference to their vocabulary and grammar knowledge. This finding is consistent with the cognitive theories of reading that treat the lexical and grammatical knowledge of learners as a major factor in distinguishing poor from competent readers. The study also confirmed previous research in finding that vocabulary knowledge was associated with reading comprehension more strongly than grammatical knowledge.
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