Measuring Readability for Learners of English as a Foreign Language by Linguistic and Learner Features

Abstract

The Internet serves as a source of authentic reading material, enabling learners to practice English in real contexts when learning English as a foreign language. An adaptive computer-assisted language learning and teaching system can assist in obtaining authentic materials such as news articles from the Internet. However, to match material level to a learner’s reading proficiency, the system must be equipped with a method to measure proficiency-based readability. Therefore, we developed a method for doing so. With our method, readability is measured through regression analysis using both learner and linguistic features as independent variables. Learner features account for learner reading proficiency, and linguistic features explain lexical, syntactic, and semantic difficulties of sentences. A cross validation test showed that readability measured with our method exhibited higher correlation (r = 0.60) than readability measured only with linguistic features (r = 0.46). A comparison of our method with the method without learner features showed a statistically significant difference. These results suggest the effectiveness of combined learner and linguistic features for measuring reading proficiency-based readability.