Abstract

Most corpus-based investigations capitalise on word list analyses: frequency, keyword, and key-keywords, in profiling the lexical features of a specialised language. Though the three word lists have been used in many corpus-based language studies, comparisons across these three types of word lists in characterising a specialised language has not been made to identify any salient information each word list can reveal about the target language. This paper provides comparisons of Engineering English using three types of word list: frequency, keyword and key-keyword lists. The purpose is to identify the lexical information that can be revealed by the groups of words listed according to each type of word lists. To conduct the analyses, a corpus of Engineering English (E 2 C) is created. All the word lists from the corpus are extracted using the Wordsmith software. Next, further analyses on the distribution of the vocabulary components, namely function vs. content words, and word categories i.e. GSL, AWL and Others, are conducted on all the three word lists. The findings reveal that different word lists result in different ranges of words, and the analyses of the words reveal the distinct features of the specialised language at different levels. Given such differences, this study provides insights into which word lists are to be considered in a lexical study for language description purposes. Hence, this study further verifies the importance of corpus-based lexical investigations in providing empirical evidences for language description. Keywords: corpus; lexical features; specialised corpus; language description; word lists analysis

Highlights

  • IntroductionIn the teaching and learning of English for Specific Purposes (ESP), the concern of many instructors is to ensure that the learners are exposed to the language that is specific to their disciplines

  • The tenet of a language description is in its words

  • It is found that the text coverage of the top 100 words from E2C and British National Corpus (BNC) is about 54% and 46% respectively; the specialised corpus has more text coverage than BNC

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Summary

Introduction

In the teaching and learning of English for Specific Purposes (ESP), the concern of many instructors is to ensure that the learners are exposed to the language that is specific to their disciplines. This involves the word and its lexical units, such as collocations and colligations. The frequency word list highlights the most frequent words in a corpus. The keyword list provides high occurrence words relative to the whole individual corpus; the words are said as to be specific to or representative of the target corpus, relative to another general corpus. The keykeywords list presents the most frequent keywords in a target corpus (Scott 1997)

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