A corpus-based study of vocabulary in massive open online courses (MOOCs)

词汇 纪律 计算机科学 名词 词汇学习 学术英语 理解力 词汇发展 数学教育 人工智能 心理学 语言学 社会学 社会科学 哲学 程序设计语言
作者
Chen-Yu Liu
出处
期刊:English for Specific Purposes [Elsevier]
卷期号:72: 40-50 被引量:1
标识
DOI:10.1016/j.esp.2023.08.002
摘要

Massive open online courses (MOOCs) provide rich academic content to learners around the world. However, understanding such content is challenging to second-language learners. Given the importance of vocabulary knowledge to comprehension, this study constructed a 10.2-million-word corpus of MOOCs from four disciplinary areas (engineering, humanities and arts, science and math, and social sciences), and examined (a) the lexical demands of MOOCs, (b) the coverage of general and discipline-specific academic vocabulary lists in MOOCs, and (c) the extent to which these lists helped learners with MOOCs' lexical demands. The results show that – together with proper nouns, marginal words, transparent compounds, and acronyms – the most frequent 3,000 and 4,000 word families of general English respectively provide 90% and 95% coverage of the corpus, indicating that MOOCs are as lexically challenging as university lectures. Also, because both general and discipline-specific academic vocabulary lists provide high coverage of MOOCs, studying them can lower students' learning burdens and help them achieve higher coverage of MOOCs than learning words by frequency. Lastly, based on learners’ existing vocabulary knowledge and target disciplines, this study provides pedagogical recommendations to teachers on how to employ general and discipline-specific academic word lists as vocabulary support for EAP students.
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