Correlation between an Entropy Based Measure and English Language Learner Proficiency

Brendan Flanagan, Sachio Hirokawa

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    It is important for education systems to analyze and provide an appropriate level of support to meet the needs of learners. An example of this is how the effectiveness of automatic language learner error detection and correction can vary depending on the learner's proficiency level. Covering a wide range of language complexity makes the task of error detection difficult. By predicting the learner's proficiency level, different error models can be applied for different proficiency levels. In this paper, we propose a measure based on the frequency of words in the sentences produced by learners during speaking exams to predict the learner's language proficiency. The proposed measure is compared to the learner's vocabulary size by correlation analysis. The results suggest that there is a stronger correlation between the proposed measure and the proficiency of the learner than the learner's vocabulary size.

    Original languageEnglish
    Title of host publicationProceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015
    EditorsSachio Hirokawa, Kiyota Hashimoto, Tokuro Matsuo, Tsunenori Mine
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages349-353
    Number of pages5
    ISBN (Electronic)9781479999583
    DOIs
    Publication statusPublished - Jan 6 2016
    Event4th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2015 - Okayama, Japan
    Duration: Jul 12 2015Jul 16 2015

    Publication series

    NameProceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015

    Other

    Other4th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2015
    CountryJapan
    CityOkayama
    Period7/12/157/16/15

    All Science Journal Classification (ASJC) codes

    • Information Systems
    • Computer Networks and Communications
    • Computer Science Applications
    • Computer Vision and Pattern Recognition

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