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An Empirical Application of ANOVA, Correlation and Regression Method in English Testing

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Intelligent Computing Theories and Applications (ICIC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7390))

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Abstract

Reading assessment is an indispensable part of language testing. Good language tests are to provide an accurate measure of learners’ language abilities. This empirical study aims to investigate whether participants’ reading performance varies when different item types are employed to elicit reading abilities and examine the relationship between item types and reading abilities. Data collection included the use of reading comprehension tests. The data were analyzed using inferential statistics (Descriptive statistics, ANOVA, Correlation and Regression). This study may provide some implications and recommendations on testing research and the reform and development of EFL teaching.

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References

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Author information

Authors and Affiliations

  1. Department of Basics, Chinese People’s Armed Police Force Academy, Langfang, Hebei, 065000, China

    Hua Wang

Authors
  1. Hua Wang
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Machine Learning and Systems Biology Laboratory, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. Faculty of Computer and Information Sciences, Hosei University, 3-7-2, Kajino-Cho, Koganei-Shi, Japan

    Jianhua Ma

  3. School of Electrical Engineering, University of Ulsan, #7-413, San 29, Muger Dong, 680-749, Ulsan, South Korea

    Kang-Hyun Jo

  4. Department of Biotechnology, Indian Institute of Technology (IIT) Madras, 600 036, Chennai, Tamilnadu, India

    M. Michael Gromiha

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Wang, H. (2012). An Empirical Application of ANOVA, Correlation and Regression Method in English Testing. In: Huang, DS., Ma, J., Jo, KH., Gromiha, M.M. (eds) Intelligent Computing Theories and Applications. ICIC 2012. Lecture Notes in Computer Science(), vol 7390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31576-3_30

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  • DOI: https://doi.org/10.1007/978-3-642-31576-3_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31575-6

  • Online ISBN: 978-3-642-31576-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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