Profiling the Academic Word List (AWL) in a financial corpus

Li, Yongyan; Qian, David D.

doi:10.1016/j.system.2010.06.015

Cited by 45 publications

(26 citation statements)

References 9 publications

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“…Two new research waves were started in reaction to the AWL. The first one consists of research studies which test the AWL's applicability in numerous academic corpora, which usually present a specific scientific area (Hyland &Tse 2007;Chen &Ge2007;Konstantakis 2007;Coxhead & Hirsch 2007;Martinez et al 2009;Vongpumivitch et al 2009;Li &Qian 2010;Yazhen& Lei 2013;Dang& Webb 2014;Liqin&Xinlu2014;Mozaffari & Moini 2014). The second wave consists of studies which aim to form their own specific word lists, usually in specific academic genres and areas (Coxhead & Hirsch 2007;Lessard-Clouston 2013;Surtees & Horst 2013;Wolfe 2015).…”

Section: Introductionmentioning

confidence: 99%

Specialized word lists: Survey of the literature: Research perspective

Palinkaševic¹

2017

Istraživanja u pedagogiji

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Section: Introductionmentioning

confidence: 99%

Specialized word lists: Survey of the literature: Research perspective

Palinkaševic¹

2017

Istraživanja u pedagogiji

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“…The AWL appeared to be most useful to students studying in the computer sciences, with 16% of the words were covered by the AWL, and least useful to biology students, with only 6.2% coverage. They concluded that although the use of a general academic word list may be attractive, there appears good reason to approach the list with caution because not all learners would receive the same benefits across diciplines.Other studies that have profiled the AWL on different corpora (Chen & Ge, 2007;Li & Qian, 2010; Martinez et al, 2009;Paquot, 2007) also concluded that the list is too general, which could expose learners to more vocabulary than they may need, while at the same time deprive learners of the specific vocabulary that would prove more beneficial. Thus, instead of teachers and learners focusing on a list that was created from a corpus based on many different subject areas, they may be better served with a list based on their area of study.…”

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confidence: 99%

Creating an Institution-Specific Science and Engineering Academic Word List for University Students

Veenstra¹,

Sato²

2018

The Journal of AsiaTEFL

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This research study considers the problem of Japanese university students who are studying the sciences in their native language, but who also may be expected to do at least part of their reading through textbooks written in English. The article presents a Science Textbook Word List (STWL), derived from a 700,000-word academic corpus compiled from English-medium textbooks intended for science majors. The STWL contains 309 word families, which accounts for 13.4% of the tokens in the science textbook corpus under study. The high word frequency and the wide text coverage of academic vocabulary throughout the science textbooks confirm that academic vocabulary plays an important role in science textbooks. The study also found that the STWL provided better coverage of the studied corpus than the widely used Academic Word List (AWL) (Coxhead, 2000), and another science word list (Coxhead & Hirsh, 2007). These results demonstrate that corpus-specific word lists provide more coverage of the intended texts with fewer items. This is of benefit to the students as the amount of learning time can be significantly reduced, and the effort put in to learn such lists is well repaid by the opportunity for using the vocabulary. Keywords: word list, lexical coverage, vocabulary, EFL IntroductionMany students enrolled as science majors in Asia attend lectures held in their first language, yet are required to read textbooks that are written in English (in Taiwan, see Hsu, 2014; in Indonesia, see Nurweni & Read, 1999; in Iran, see Valipouri & Nassaji, 2013; and in Thailand, see Ward, 2009). As knowledge of academic vocabulary is seen as an indispensable component of both academic reading ability and success (Dreyer & Nel, 2003;Nagy & Townsend, 2012;Schmitt, Jiang, & Grabe, 2011), it is imperative for learners to comprehend what is read. Unfortunately, due to the large amount of vocabulary found in English-medium academic texts, expecting students to know or learn this vast quantity of words may prove to be an unrealistic assumption of the teachers.One way to assist science majors with reading comprehension is to narrow the domain of language, providing learners with the specific lexical knowledge necessary to function in such an academic context. Nation (2001, 2008) recommends that students with lower-levels of English should focus on the general high-frequency vocabulary, such as West"s (1953) General Service List (GSL), while higher-level students who already have a strong command of the basic core vocabulary, such as many science majors, should focus on the lower frequency technical or academic vocabulary.Technical or domain-specific words are vocabulary related to a particular discipline (Martin, 1976).Jay Veenstra et al.The Journal of Asia TEFL Vol. 15, No. 1, Spring 2018, 148-166 149These items occur frequently in a specialized text of a subject area, but do not occur (or very rarely occur) in other fields (Nation, 2001). For example, words such as torque, thermodynamics, concave, refraction, and electroscope are examples o...

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“…The poor coverage provided by AWL in Hinck's (2003) study (2.4%) is perhaps because the academic corpus which was analyzed was different (presentations speech) and produced by non native English speakers (Swedish speakers). Notably, the coverage figure of the AWL in this study is quite low compared with its coverage in studies of academic written corpora, for example, 10.07% (Chen & Ge, 2007), 10.0% (Coxhead, 2000), 11.6% (Cobb & Horst, 2004), 10.6% (Hyland & Tse, 2007), 10.46% (Li & Qian, 2010), 9.06% (Martínez et al, 2009), 11.17% (Vongpumivitch et al, 2009) and 11.3% (Ward, 2009). The low coverage of the AWL in academic spoken discourse is likely because the AWL was derived from academic written texts, which emphasizes the view suggesting that the nature of word list mirrors the nature of the corpus it was developed from (Nation, 2016;Schmitt, 2010).…”

Section: Is the Coverage Of The Awl In Lectures Different From That Imentioning

confidence: 62%

“…They criticized the assumption that "there is a general vocabulary of value to all students preparing for, or engaged in, university study" (p. 248). However, other studies on the coverage of academic words in discipline specific corpora (Chung & Nation, 2004;Li & Qian, 2010;Martinez, Beck & Panza, 2009;Vongpumivitch, Huang, & Chang, 2009;Ward, 2009) indicate the supportive role of the AWL in academic texts.…”

Section: The Academic Word List (Awl)mentioning

confidence: 98%

A Corpus-Based Investigation of Academic Vocabulary and Phrasal Verbs in Academic Spoken English

Aldohon¹

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Academic spoken language is capturing the attention of many vocabulary researchers in recent years (Rodgers & Webb, 2016;Thompson, 2005). In turn, research has focused on assessing word lists to promote second language learners' comprehension of academic speech (Dang & Webb, 2014). The present thesis is comprised of two corpus-based studies investigating academic spoken discourse. The first study examined (1) the vocabulary demands of spoken academic English and (2) the coverage of Coxhead's (2000) Academic Word List (AWL) in spoken Academic English. Transcripts of 62 lectures and 7 seminars form the Michigan Corpus of Academic Spoken English (MICASE) were collected and analyzed. The findings suggested that coupled with proper nouns and marginal words, knowledge of the most frequent 3,000 or 7,000 word families is needed to reach 95.55% and 98.03% coverage respectively of the combined lectures and seminars corpus. The AWL provided 3.68% coverage of the combined seminars and lectures corpus. The second study compared the lexical coverage of Garnier and Schmitt's (2015) phrasal verb list (PHaVE List) with the most frequent 150 AWL lemmatized verbs in academic spokenEnglish. The analysis was carried out on a 2,431,351 running-word corpus created from the British Academic Spoken English (BASE) and the MICASE corpora. The finding indicated that the PHaVE List accounted for slightly higher coverage figures than the AWL in the study corpus. Pedagogical implications were made for English for academic purposes teachers, learners and material designers.ii

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Profiling the Academic Word List (AWL) in a financial corpus

Cited by 45 publications

References 9 publications

Specialized word lists: Survey of the literature: Research perspective

Specialized word lists: Survey of the literature: Research perspective

Creating an Institution-Specific Science and Engineering Academic Word List for University Students

A Corpus-Based Investigation of Academic Vocabulary and Phrasal Verbs in Academic Spoken English

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