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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.

基于语料库的小学英语认识率及教材选词策略研究

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