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Making useful wordlists for ELT Topical vocabulary from the WWW Simon Smith & Scott Sommers Ming Chuan University, Taipei Adam Kilgarriff, Lexical Computing.

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Presentation on theme: "Making useful wordlists for ELT Topical vocabulary from the WWW Simon Smith & Scott Sommers Ming Chuan University, Taipei Adam Kilgarriff, Lexical Computing."— Presentation transcript:

1 Making useful wordlists for ELT Topical vocabulary from the WWW Simon Smith & Scott Sommers Ming Chuan University, Taipei Adam Kilgarriff, Lexical Computing Ltd, UK Generous support from National Science Council, Taiwan

2 Outline Importance of learning natural English Wordlists in English learning Making relevant wordlists Using two corpus analysis tools – WebBootCat – Sketch Engine Conclusions and future plans

3 The problem Learning non-authentic English – It’s raining cats and dogs! – Long time no see! In Taiwan, all students learn these They may believe they are authentic But English speakers hardly use them!

4 Word and phrase lists Students must learn vocabulary It is best to learn vocabulary through practice: – Reading – Speaking to American people – Interacting in the language That is difficult for Asian students In Taiwan, students must learn vocabulary from lists

5 From the MOE 6000 word high school list – Probably useful for policy makers – May be useful for teachers – Not useful for learners Better to organize wordlists by topic?

6 So, we should teach vocabulary by topic? Khmer learning Game © North Illinois University

7 Unit 1 Getting started at University Nouns attendance course facilities helmet initiativemajor vendor Verbs accomplishconsider improve tease Adjectives challenging fortunate impatient occasional protective From the ELC textbook It is not easy to make up a good vocabulary list for an abstract topic Try these topics: – Unit 1: Getting started at University – Unit 2: Family and Hometown – Unit 3: English and You Please – Choose a topic – Write down some good keywords Better use computer to help us!

8 Getting wordlists from the web

9 WebBootCat: making corpora from the web User chooses some seed words – For example freshman and university WebBootCat – searches Yahoo for seed words – throws away lists of numbers, HTML, prices lists… – puts all running text into a corpus – tags the corpus (noun, verb etc) if required

10 12345 56789 $$$$$ £££££ *&%^ WebBootCat passes query to Yahoo! WebBootCat throws away non-data web pages WebBootCat puts text pages in corpus User enters seed words

11 Now, we can use Sketch Engine software to make a concordance

12 Or, we can make a wordlist, using WebBootCat

13 Now, we can bootstrap a new wordlist. We use the first wordlist as seed words for the second one.

14 Now, let’s make a list of multi- word terms.

15 Advantages of automatic wordlist creation contain relevant, topical vocabulary created easily and conveniently of course, we can select the words manually, from the automatic list!

16 Disadvantages of manual wordlist creation It is difficult to get inspiration to make good wordlists manually. Manual wordlists may include rare or unnecessary vocabulary.

17 Future work: Automatic cloze exercise generation Q: It’s a ___ day today! (b) tepid (a) toasty Choose: (c) lukewarm (d) sunny

18 Summary: making wordlists choose a topic get a topic corpus from the web extract topic wordlist from it Use recursive bootstrapping to extend the wordlist include multi-word terms in the wordlist

19 Thank you www.sketchengine.co.uk


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