Abstract
Acquiring vocabulary is important when studying English, as it assists in listening, speaking, reading, and writing. In this paper, we develop an English webpage corpus (EWC) and create a word frequency list using web crawler technology. By comparing EWC word lists with the British National Corpus (BNC), we find that the BNC word frequency list possesses the feature of timeliness. We also explore primary school students’ English word recognition rates by comparing the word frequency lists of several corpora, including EWC, BNC, SUBTLEX-US, and Subtitle Corpus of Children’s BBC (CBBC). The results show that the word recognition rates for primary school children are relatively low in both general language and specific language register. Motivated by the experiment results, we finally propose some word-selection strategies for compiling English textbooks for Chinese primary school students.
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Acknowledgements
We thank the reviewers for their helpful comments and suggestions. We also appreciate Xiong-fei XU and Zhi-ming CHEN for assistance with the experiments, and Dr. Jin-shan ZENG and Dr. Hong-wei LI for valuable discussion.
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Project supported by the National Natural Science Foundation of China (Nos. 61272212, 61462043, and 61462045) and the Graduates Innovation Fund of Jiangxi Normal University, China
ORCID: Wen-yan XIAO, http://orcid.org/0000-0001-6253-2414
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Xiao, Wy., Wang, Mw., Weng, Z. et al. Corpus-based research on English word recognition rates in primary school and word selection strategy. J. Zhejiang Univ. - Sci. C 18, 362–372 (2017). https://doi.org/10.1631/FITEE.1601118
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DOI: https://doi.org/10.1631/FITEE.1601118