NotesFAQContact Us
Search Tips
Peer reviewed Peer reviewed
Direct linkDirect link
ERIC Number: EJ1099261
Record Type: Journal
Publication Date: 2016
Pages: 22
Abstractor: As Provided
ISSN: ISSN-1062-7197
Does EFL Readers' Lexical and Grammatical Knowledge Predict Their Reading Ability? Insights from a Perceptron Artificial Neural Network Study
Aryadoust, Vahid; Baghaei, Purya
Educational Assessment, v21 n2 p135-156 2016
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.
Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Iran (Tehran)
Identifiers - Assessments and Surveys: Test of English as a Foreign Language
Grant or Contract Numbers: N/A