Lexical Features of Engineering English vs. General English
Bibliographic Data
| ID | 21185266 |
|---|---|
| Authors | Noorli Khamis (0000-0003-3934-1489, Technical University of Malaysia Malacca), Imran Ho Abdullah (0000-0003-0909-1802, National University of Malaysia), Imran Ho-Abdullah |
| Year | 2017 |
| Volume | 17 |
| Issue | 3 |
| Pages | 106-119 |
| Publication date | 2017-08-28 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | GEMA Online Journal of Language Studies (JOURNAL) |
| Journal identifiers | ISSN: 1675-8021 • E-ISSN: 2550-2131 |
| Publisher | Penerbit Universiti Kebangsaan Malaysia (UKM Press) (PUBLISHER) |
| DOI | 10.17576/gema-2017-1703-07 |
| OpenAlex | W2749960524 |
| Language | EN |
| References cited | 6 |
The knowledge on the features of the English varieties is essential to understand the differences and similarities of the varieties for second language teaching and learning, either for general proficiency (EGP) or English for Specific Purposes (ESP) classes. This paper demonstrates a corpus-based comparison of the lexical features between an ESP variety (Engineering English) and a General English (GE). Two corpora are used in the study; the Engineering English Corpus (EEC) acts as the representation of the specialized language, and the British National Corpus (BNC) as the General English (GE). The analyses are conducted by employing the WordList functions of a linguistic software – Wordsmith. Discussions on the differences (or similarities) of these two corpora include general statistics, text coverage and vocabulary size. The empirical findings in this study highlight the general lexical features of both corpora. The analyses verify that the Engineering English has less varied vocabulary, but higher text coverage than the GE; in other words, most of the words are used repeatedly throughout the EEC. Thus, this study further emphasizes the importance of corpus-based lexical investigations in providing empirical evidences for language description
British National Corpus · Corpus linguistics · Empirical research · English language · Lexical density · Lexical item · Linguistics · Natural language processing · Text corpus · Vocabulary · Computer Science · linguistics and terminology studies · Mathematics · Natural Language Processing Techniques · Second Language Acquisition and Learning · Artificial Intelligence
University Language
Textual Patterns
The Effect of Linguistic Context on EFL Vocabulary Learning
The Effects of Word Exposure Frequency on Incidental Learning of the Depth of Vocabulary Knowledge
Where would general service vocabulary stop and special purposes vocabulary begin
A reassessment of frequency and vocabulary size in L2 vocabulary teaching
| Highly cited | No |
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