The Plate of Mangoes

Over the years, substantial shifts in theory, belief, and practice have occurred in the teaching of language, specifically vocabulary, grammar, or their combination in lexicogrammatical features of a language as part of the writing class or curriculum (Paltridge, 2004;. Much of the instruction in L2 writing for adult learners who are preparing for degree study in an English-medium college or university focuses on academic writing; one result of this interest in academic writing is a growing body of research data that provides insights into the language of academic discourse and the various registers that make up that discourse, demonstrating that vocabulary and associated grammar characterize particular discourse types (. Through knowledge of that literature and the development of skill at analyzing particular examples of academic writing, teachers can learn to identify the language that their students need to become fluent writers of various types of English academic prose. In this article, we review recent scholarship on the nature of the vocabulary and grammar that characterize academic writing. In addition to the discussion of published research and theory on language-in-use focused on academic prose, we also include a selected listing of web-based resources to be used for teacher development. We also suggest practical ways that teacher educators can bring the study of academic language into the preparation of writing teachers to teach the vocabulary and grammar of academic prose. #

Section B; Tasks TESOL Diploma program, Module-4, Assignment -2

This research article is a parallel study to Coxhead’s original “Academic Word List” study. Coxhead’s based her study on written texts and therefore I examined oral academic texts for comparison. I analyzed nearly one million words of oral text to determine what vocabulary English learners are more likely to encounter in a English-based university setting. Roughly, I find that many academic vocabulary items are in agreement with Coxhead’s findings, however, where Coxhead claims that academic vocabulary accounts for roughly 10% of all academic input, my research shows that for oral academic input it really only accounts for 3-6%.

The objective of this corpus-based lexical study was to investigate academic words (AW) families occurring in the corpus of laboratory animal research articles (LARAs). The corpus included 160 LARAs during the year 2010 to 2014 from the journal of the Institute for Laboratory Animal Research (ILAR). The research instruments used for analyzing AW families were "AntConc Version 3.4.3" and "the RANGE program". The corpus constituted 840,773 word tokens and 22,434 word types. Three criteria of Coxhead including "specialized occurrence", "range", and "frequency" were used for analyzing the academic words. Frequency and percentages were used to analyze the data in the corpus. The results revealed that word families of academic word list (AWL) were identified 768 AWL word families (4.36% of text coverage). The word families of AWL in LARA corpus will be used for ESP pedagogy in the field of laboratory animal.

Word lists present an essential tool in vocabulary teaching. Compilation of specific word lists for various fields is one of the most prominent branches of research in this field at the moment. New methodological changes in word list formation have been proposed because of the appearance of the New-GSL (Brezina&Gablasova, 2013) and AVL (Gardner & Davies, 2013).The aim of this paper is twofold. The first one is to present a word list overview which would reflect how these changes have affected the field so far. The second is to serve as a methodological guide for future researchers interested in specific word list formation. The paper provides an overview of the two most significant word lists the GSL (West, 1953) and AWL (Coxhead, 2000) along with their proposed replacements, detailed information about seven specific word lists, which were published from 2013 to 2016, with a specific focus on corpus formation criteria, word selection criteria and validity and relevance testing.

h i g h l i g h t s

This study investigates the usefulness of two academic word lists -Coxhead's (2000) Academic Word List (AWL) and Gardner & Davies' (2014) Academic Vocabulary List (AVL) -for students of English for Chinese Medical Purposes. The two academic word lists were evaluated in terms of the coverage they achieved in a corpus of Chinese medical research articles (CMRAs) written in English. The AWL was found to cover 10.64% of tokens in the corpus, while the AVL was found to cover 21.17% overall. In both cases, the majority of the coverage was achieved by a relatively small subset of the lexical items on the lists. Analysis of the most frequently used words that are not included in the General Service List, Academic Word List and Academic Vocabulary List in the CMRAs shows that a small number of such words achieve a high level of coverage, suggesting that they should be given a great deal of attention by learners in this discipline. This suggests that a discipline-specific listing would be of great benefit to learners in this discipline. A list of the most prominent 100 off-list lexical items is provided.

The Academic Word List Corpus studies Vocabulary frequency a b s t r a c t This study investigated (a) the lexical demands of academic spoken English and (b) the coverage of the Academic Word List (AWL) in academic spoken English. The researchers analyzed the vocabulary in 160 lectures and 39 seminars from four disciplinary sub-corpora of the British Academic Spoken English (BASE) corpus: Arts and Humanities, Life and Medical Sciences, Physical Sciences and Social Sciences. The results showed that knowledge of the most frequent 4,000 word families plus proper nouns and marginal words provided 96.05% coverage, and knowledge of the most frequent 8,000 word families plus proper nouns and marginal words provided 98.00% coverage of academic spoken English. The vocabulary size necessary to reach 95% coverage of each sub-corpus ranged from 3,000 to 5,000 word families plus proper nouns and marginal words and 5,000 to 13,000 word families plus proper nouns and marginal words to reach 98% coverage. The AWL accounted for 4.41% coverage of academic spoken English. Its coverage in each sub-corpus ranged from 3.82% to 5.21%. With the help of the AWL, learners with knowledge of proper nouns and marginal words will need a vocabulary of 3,000 and 8,000 word families to reach 95% and 98% coverage of academic spoken English, respectively.

Linguística de corpus : perspectivas, 2018

The aim of this chapter is to present an investigation on how Brazilian students use academic vocabulary. The following research questions are addressed: a) What is the vocabulary profile of assignments written by Brazilian students?; b)How does it compare to the vocabulary profile of other academic corpora?; c)What words in the AWL do Brazilian students use?, and d) How does the use of academic words differ between Brazilian students and students represented in the British Academic Written English (BAWE) corpus? To answer these questions, the Brazilian Academic Written English (BrAWE) corpus was analysed using Range and Sketch Engine. The results point that BrAWE presents a similar number of academic words as other academic corpora. However, the word forms selected by these students differ as they underuse affixation processes.

This study is a corpus-based lexical study that is aimed at comparing semi-technical vocabulary and technical vocabulary to address the specific needs of undergraduates majoring in information engineering in mainland China through the study of bilingual specialized courses. A 1,024,882word corpus of Information Engineering English Corpus (IEEC) was built using texts from ten specialized courses. Semi-technical and technical vocabulary items were profiled using West's (1953) General Service List and Coxhead's (2000) Academic Word List. A quantitative analysis was carried out to find the optimal frequency threshold for high-frequency academic/semitechnical and technical vocabulary specific to the discipline of Information Engineering. As a result, 248 semi-technical and 166 technical word families were extracted covering 9.16% and 4.95% of the total tokens of the corpus. The pilot study further explored the selected vocabulary of varying specificity in terms of their lexical features as well as collocations and found that there is a continuum rather than distinct boundaries between the GSL, discipline-specific academic and technical words when they are manipulated to serve specific purposes.