Developmental features of multi-word expressions in spoken discourse by Chinese learners of English

Multi-word expressions (MWEs) serve as vital indicators of language development and have been a primary focus in second language acquisition research. The use of MWEs in spoken discourse, however, remains relatively under-explored. To address this gap, this study aims to investigate the current status and developmental features of MWE use in spoken English by Chinese learners of English across three proficiency levels based on Nattinger and DeCarricos’ classification framework of MWEs. A comparative analysis of MWE usage patterns across these groups yields two key findings: (1) The overall proficiency in using MWEs is relatively low, marked by an imbalance and inaccuracy in MWE types. Specifically, learners exhibit minimal use of “polywords” and “institutionalised expressions” within the structural dimension, and “discourse devices” and “social interactions” within the functional dimension. Moreover, learners demonstrate a high error rate across various MWE types. (2) Although the overall proficiency in using MWEs shows no significant improvement across the three levels, an upward trend is observed in the usage of overall tokens, types, and various categories of MWEs in both dimensions, culminating in a significant increase in the variation of MWEs at the highest proficiency level. Drawing upon these findings, this study proposes several pedagogical implications for enhancing the teaching and learning of MWEs in spoken discourse.

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Publication Details

Journal
Humanities and Social Sciences Communications
Published
2024-12-18
DOI
https://doi.org/10.1057/s41599-024-04206-8
Citations
1
Primary Topic
Second Language Acquisition and Learning
Type
article
Field-Weighted Citation Impact
0.79

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Developmental features of multi-word expressions in spoken discourse by Chinese learners of English

Xiao Wang, Huiping Zhang
1 citations
Humanities and Social Sciences Communications
Second Language Acquisition and Learning
0.79
article

Developmental features of multi-word expressions in spoken discourse by Chinese learners of English

Xiao Wang, Huiping Zhang
article en
1 citations

Abstract

Multi-word expressions (MWEs) serve as vital indicators of language development and have been a primary focus in second language acquisition research. The use of MWEs in spoken discourse, however, remains relatively under-explored. To address this gap, this study aims to investigate the current status and developmental features of MWE use in spoken English by Chinese learners of English across three proficiency levels based on Nattinger and DeCarricos’ classification framework of MWEs. A comparative analysis of MWE usage patterns across these groups yields two key findings: (1) The overall proficiency in using MWEs is relatively low, marked by an imbalance and inaccuracy in MWE types. Specifically, learners exhibit minimal use of “polywords” and “institutionalised expressions” within the structural dimension, and “discourse devices” and “social interactions” within the functional dimension. Moreover, learners demonstrate a high error rate across various MWE types. (2) Although the overall proficiency in using MWEs shows no significant improvement across the three levels, an upward trend is observed in the usage of overall tokens, types, and various categories of MWEs in both dimensions, culminating in a significant increase in the variation of MWEs at the highest proficiency level. Drawing upon these findings, this study proposes several pedagogical implications for enhancing the teaching and learning of MWEs in spoken discourse.

Humanities and Social Sciences CommunicationsVol. 11(1)
Northeast Normal University (CN)
National Social Science Fund of China
Quality Education
Openalex Percentile: Top 21%
Second Language Acquisition and Learning
0.79
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Developmental features of multi-word expressions in spoken discourse by Chinese learners of English — Xiao Wang, Huiping Zhang · Humanities and Social Sciences Communications (2024) | TGRS Research Map | TGRS