A Corpus-Based Study of Four-Word Lexical Bundles in Chinese and U.S Phd Dissertations

Min Chen, Roslina Abdul Aziz and Syamimi Turiman
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Min Chen: Academy of Language Studies, Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia; School of Social Management, Jiangxi College of Applied Technology, 2 Wenfeng Road, Ganzhou, Jiangxi Province, 314000, China
Roslina Abdul Aziz: Akademi Pengajian Bahasa, Universiti Teknologi MARA Cawangan Pahang, Kampus Jengka,26400 Bandar Jengka, Pahang, Malaysia
Syamimi Turiman: Akademi Pengajian Bahasa, Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia

International Journal of Research and Innovation in Social Science, 2024, vol. 8, issue 11, 1668-1681

Abstract: Lexical bundles (LBs), which are crucial for smooth language articulation, are deemed a significant unique characteristic in scholarly writing. Many PhD students find that their English academic writing output often falls short of academic expectations compared to native language academic authors in terms of vocabulary sophistication. This study aimed to examine both the functional commonalities and variances in the usage patterns of four-word lexical clusters among Chinese PhD postgraduate EFL students (CH-PhD) and their American counterparts (US-PhD). The study adopted a corpus-based approach, relying on two self-built learner corpora (CH-PhD and US-PhD), and incorporated both quantitative and qualitative data analysis methods. Using AntConc’s N-gram tool, 72 bundles in CH-PhD and 37 in US-PhD were extracted. Findings indicate that Chinese PhD students employed a greater number of four-word word clusters in their academic writings. As for the functional types, Chinese PhD learners are more inclined to use research-oriented bundles to provide descriptions to organise writer’s actions, while native American PhD students are more inclined to use text-oriented bundles to organise the text. Furthermore, the findings illuminate methods to improve the instruction of LBs in China’s academic writing curriculum.

Date: 2024
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