EFL learner reading time model for evaluating reading proficiency

Authors:
Katsunori Kotani;Takehiko Yoshimi;Takeshi Kutsumi;Ichiko Sata;Hitoshi Isahara
Affiliations:
Kansai Gaidai University, Hirakata, Osaka, Japan and National Institute of Information and Communications Technology, Kyoto, Japan;Ryukoku University, Otsu, Shiga, Japan and National Institute of Information and Communications Technology, Kyoto, Japan;Sharp Corporation, Yamatokoriyama, Nara, Japan;Sharp Corporation, Yamatokoriyama, Nara, Japan;National Institute of Information and Communications Technology, Kyoto, Japan
Venue:
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
Year:
2008

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Reading level assessment using support vector machines and statistical language models

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics

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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.