| Author: | Fu, Fuling |
| Title: | Corpus analysis of the vocabulary of the Chinese national matriculation English test |
| Advisors: | Lin, Phoebe (ENGL) |
| Degree: | M.A. |
| Year: | 2020 |
| Subject: | Discourse analysis English language -- Study and teaching -- Chinese speakers English language -- Ability testing Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of English |
| Pages: | viii, 171 pages : color illustrations |
| Language: | English |
| Abstract: | A corpus-based study was performed to provide an overview of the words in the Chinese National Matriculation English Test (NMET). The study aims to guide students struggling with preparing themselves for the test because of their limited vocabulary. A corpus, consisting of 117 thousand words and covering national and regional specific papers from 2015 to 2019 except those used in Shanghai, Taiwan, Hong Kong and Macau, was created to conduct the research. Using the corpus analysis tool AntConc and Wmatrix4, and reference corpus - the British National Corpus (BNC) Sampler Written, the research was conducted. First, teachers and students can prioritize the word families with high range value and utilize either national or regional specific papers to prepare students for the NMET. Besides, the lexical differences between the national and regional specific NMET papers are consistent with regional development and instructive for teachers, advanced learners, and other stake holders such as textbook developers. The unusual lexical frequency compared with the BNC Sampler Written presents the specific characteristics of the test and test developers' tendency to encourage college and university candidates to get prepared for their further education. The NMET is authentic and instructive for English education in China. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 5143.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.14 MB | Adobe PDF | View/Open |
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