Does EFL Readers' Lexical and Grammatical Knowledge Predict Their Reading Ability? Insights From a Perceptron Artificial Neural Network Study

被引:21
作者
Aryadoust, Vahid [1 ]
Baghaei, Purya [2 ]
机构
[1] Natl Univ Singapore, Singapore, Singapore
[2] Islamic Azad Univ, Tehran, Iran
关键词
D O I
10.1080/10627197.2016.1166343
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
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.
引用
收藏
页码:135 / 156
页数:22
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