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Learner Feature Variation in Measuring the Listenability for Learners of English as a Foreign Language

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Emerging Technologies for Education (SETE 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10108))

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Abstract

Previous research on the ease of listening comprehension (henceforth, listenability) has measured listenability on the basis of sentence properties such as the length of words/sentences and speech rate. Recent research has included features of listeners, which are required for the measurement of listenability for English learners because their listening proficiencies vary greatly from the beginner to the advanced level. Given the importance of listening proficiency as a listener feature, this study developed listenability measurement methods based on the costs of compiling listener features: expensive features extracted from test scores and inexpensive features extracted from learners’ experiences. The experimental results showed that inexpensive features made substantial contributions to the measurement of middle-range listenability.

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Acknowledgments

This work was supported by JSPS KAKENHI Grant Numbers, 22300299, 15H02940.

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Authors and Affiliations

  1. Kansai Gaidai University, Osaka, Japan

    Katsunori Kotani

  2. Ryukoku University, Shiga, Japan

    Takehiko Yoshimi

Authors
  1. Katsunori Kotani
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  2. Takehiko Yoshimi
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Corresponding author

Correspondence to Katsunori Kotani .

Editor information

Editors and Affiliations

  1. National Yunlin University of Science and Technology, Yunlin, Taiwan

    Ting-Ting Wu

  2. Free University of Bozen-Bolzano, Rome, Italy

    Rosella Gennari

  3. National Cheng-Kung University, Tainan, Taiwan

    Yueh-Min Huang

  4. The Education University of Hong Kong, Hong Kong, Hong Kong

    Haoran Xie

  5. MC Information Multimedia Communication AG, Saarbrücken, Germany

    Yiwei Cao

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Kotani, K., Yoshimi, T. (2017). Learner Feature Variation in Measuring the Listenability for Learners of English as a Foreign Language. In: Wu, TT., Gennari, R., Huang, YM., Xie, H., Cao, Y. (eds) Emerging Technologies for Education. SETE 2016. Lecture Notes in Computer Science(), vol 10108. Springer, Cham. https://doi.org/10.1007/978-3-319-52836-6_36

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  • DOI: https://doi.org/10.1007/978-3-319-52836-6_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52835-9

  • Online ISBN: 978-3-319-52836-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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