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An Empirical Study on Wrongly Written or Mispronounced Characters in Hanyu Shuiping Kaoshi Compositions from the Perspective of Readability Research

Published: 18 November 2022 Publication History

Abstract

In the study of Hanyu Shuiping Kaoshi (HSK) composition, there is a lack of research on the quantitative form of wrongly written or mispronounced character (WWMC). This paper chooses the readability perspective to quantitatively study the influence of WWMCs in HSK compositions. Through the construction of HSK composition readability corpus, they are composed of 5498 HSK compositions carefully rated by experts. Through quantitative research, it is found that the lower the grade is, the more the number of compositions without WWMCs; With the increase of text readability, the proportion of WWMCs in the text decreases gradually, while the number of articles with WWMCs increases. With the help of the formula of HSK composition readability grade constructed by multiple linear regression, it is found that the WWMC's weight is -0.0250014, which has little effect on the readability grade of HSK composition. Although the WWMC feature does not play an important role in the readability formula, we can't ignore it in the reading and writing process of HSK compositions.

References

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Yunhua Liao. 2019. The Survey and Analysis of the new HSK 5 Writing test and its Comparision with the Syllabus. Master Thesis, School of Art, Soochow University. (in Chinese) https://doi.org/10.27351/d.cnki.gszhu.2019.000628
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Tingting Liu. 2020. The Comparative Research on Chinese Character's Writing Errors of Advanced Grade Japanese and South Korean Students Based on BCC Corpus. Master Thesis, College of International Exchange and Education, Hebei University. (in Chinese) https://doi.org/ 10.27103/d.cnki.ghebu.2020.001604
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Borong Huang, Xudong Liao. 2007. Modern Chinese (Fourth Edition). Higher Education Press, Beijing, China. page 171. (in Chinese)
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Yuanyuan Dai. 2007. On the Establishment of the Database of Wrongly Written/Used Characters by Western Students & a Preliminary Survey Based on the Database. Master Thesis, Beijing Language and Culture University. (in Chinese)
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Shujun Zhou. 2012. A Research of Chinese Character Teaching Material based on HSK Dynamic Essay Corpus. Master Thesis, School of Art, Jilin University. (in Chinese)
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Zhizhi Liang. 2012. Error Analysis of Foreign Students’ Pictophonetic Characters based on HSK Dynamic Composition Corpus. Journal of Guangxi College of Education, 3(June 2012), 56-58+91. (in Chinese)
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Yongquan Li. 2020. An Empirical Study on the Readability of Chinese Text Based on Chinese Textbook Corpus. PhD Thesis, College of Chinese Language and Culture, Jinan University. (in Chinese)
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Yongquan Li. 2022. Research on Readability Grade Formula Based on HSK Compositions. In Proceedings of 4th International Conference on Natural Language Processing (ICNLP2022). Institute of Electrical and Electronics Engineers Inc. (in publishing)
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Dale Edgar and Jeanne S. Chall. 1948. A Formula for Predicting Readability: Instructions. Educational Research Bulletin 27, 2(Feb 1948), 37-54.

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  1. An Empirical Study on Wrongly Written or Mispronounced Characters in Hanyu Shuiping Kaoshi Compositions from the Perspective of Readability Research

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    ICEMT '22: Proceedings of the 6th International Conference on Education and Multimedia Technology
    July 2022
    482 pages
    ISBN:9781450396455
    DOI:10.1145/3551708
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 18 November 2022

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    Author Tags

    1. Composition
    2. Empirical research
    3. Mispronounced character
    4. Readability
    5. Wrongly written character

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