Abstract
We propose a reading time model for learners of English as a foreign language (EFL) that is based on a learner’s reading proficiency and the linguistic properties of sentences. Reading proficiency here refers to a learner’s reading score on the Test of English for International Communications (TOEIC), and the linguistic properties are the lexical, syntactic and discourse complexities of a sentence. We used natural language processing technology to automatically extract these linguistic properties, and developed a model using multiple regression analysis as a learning algorithm in combining the learner’s proficiency and linguistic properties. Experimental results showed that our reading time model predicted sentence-reading time with a 22.9% error rate, which is lower than the models constructed based on linguistic properties proposed in previous studies.
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Kotani, K., Yoshimi, T., Kutsumi, T., Sata, I., Isahara, H. (2008). EFL Learner Reading Time Model for Evaluating Reading Proficiency. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2008. Lecture Notes in Computer Science, vol 4919. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78135-6_56
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DOI: https://doi.org/10.1007/978-3-540-78135-6_56
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