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Corpus-based vocabulary analysis of English Podcasts

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dc.contributor.author Ulugbek Nurmukhamedov, Shoaziz Sharakhimov
dc.date.accessioned 2021-12-28T12:22:35Z
dc.date.available 2021-12-28T12:22:35Z
dc.date.issued 2021
dc.identifier.uri http://repository.tma.uz/xmlui/handle/1/1260
dc.description.abstract In addition to movies, television programs, and TED Talks presentations, podcasts are an increasingly popular form of media that promotes authentic public discourse for diverse audiences, including university professors and students. However, English language teachers in the English as a second language/English as a foreign language contexts might wonder: “How do I know that my students can handle the vocabulary demands of podcasts?” To answer that question, we have analyzed a 1,137,163-word corpus comprising transcripts from 170 podcast episodes derived from the following popular podcasts: Freakonomics; Fresh Air; Invisibilia; Hidden Brain; How I Built This; Radiolab; TED Radio Hour; This American Life; and Today Explained. The results showed that knowledge about the most frequent 3000 word families plus proper nouns (PN), marginal words (MW), transparent compounds (TC), and acronyms (AC) provided 96.75% coverage, and knowledge about the most frequent 5000 word families, including PN, MW, TC, and AC provided 98.26% coverage. The analysis also showed that there is some variation in coverage among podcast types. The pedagogical implications for teaching and learning vocabulary via podcasts are discussed en_US
dc.language.iso en en_US
dc.subject Lexical coverage, vocabulary profiling, podcasts, vocabulary instruction en_US
dc.title Corpus-based vocabulary analysis of English Podcasts en_US
dc.type Article en_US


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