Lexical coverage in science popularization discourse: The case of popular science news from Scientific American

被引:1
|
作者
Yu, Hong [1 ]
Wen, Ju [2 ]
机构
[1] Southwest Petr Univ, Chengdu, Peoples R China
[2] Chengdu Jincheng Coll, Chengdu, Peoples R China
关键词
Science popularization discourse; Popular science news; Academic reading materials; Scientific American; Lexical coverage; Language teaching; TED TALKS; ACADEMIC VOCABULARY; RESEARCH ARTICLES; ENGLISH; TEXTBOOKS; PROFILE; EXPERTS; GENRE; TEXT;
D O I
10.1016/j.esp.2024.10.001
中图分类号
H0 [语言学];
学科分类号
030303 ; 0501 ; 050102 ;
摘要
Science popularization discourse offers valuable reading materials for second language (L2) learners in English for Academic Purposes (EAP) contexts. However, the lexical demands of these materials remain largely unexplored. To address this gap, this study examines the lexical profile of Scientific American (SA), one of the most widely read popular science publications. Based on a corpus of popular science news collected from the SA website, we analyzed its lexical demand in terms of Nation's (2018) BNC/COCA word frequency lists and West's (1953) General Service List of English Words (GSL) plus Coxhead's (2000) Academic Word List (AWL). Our results indicate that to achieve minimal comprehension of popular science news published in SA, learners should be familiar with approximately 5,000 word families, while optimal comprehension requires knowledge of around 10,000 word families, including proper nouns, marginal words, transparent compounds, and acronyms. Notably, the GSL covers 77.55% and the AWL covers 7.08% coverage of the SA corpus, suggesting that our SA corpus has a higher coverage of general English words and a lower coverage of academic English words than university-level academic written texts. These findings highlight the potential value of popular science news in supporting academic reading, particularly for beginning EAP learners who may find these materials less lexically demanding than research articles. Pedagogical implications for incorporating popular science news into EAP courses are also provided. (c) 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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页码:45 / 55
页数:11
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