Acquisition of Valency Patterns of English Cognitive Attitude Verbs by Chinese EFL Learners: A Corpus-Driven Study

Valency reflects the governing ability of lexical items, detailing their syntactic and semantic relationships within sentences. Studying verb valency enhances our understanding of language use and provides insights into second language acquisition. While substantial research has been conducted on learners’ second language acquisition of English verb valency, issues remain. Most studies rely on written corpora, overlooking spoken language data. Additionally, many focus on a specific verb, which limits the analysis of learners’ acquisition patterns across a broader range. This study adopts the SWECCL (Version 2.0) as the observation corpus and the BNC as the reference corpus to explore valency patterns of think, believe, consider, and prefer among Chinese ELF learners in both spoken and written corpora. Results show that Chinese learners exhibit distinct valency preferences compared to L1 speakers, resulting in overuse, underuse, and misuse. Notably, they often place animate subjects before think and believe, a pattern not observed in L1 speakers. These differences arise from second language exposure, mother tongue transfer, and cultural difference. The findings provide a comprehensive description of verb valency patterns, aiding learners in understanding valency patterns of VCAs and minimizing errors. Additionally, these insights have significant implications for foreign language teaching, particularly in vocabulary instruction.

Authors

Institutions

Publication Details

Journal
Studies in English Language Teaching
Published
2024-12-11
DOI
https://doi.org/10.22158/selt.v12n4p114
Primary Topic
Second Language Acquisition and Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Acquisition of Valency Patterns of English Cognitive Attitude Verbs by Chinese EFL Learners: A Corpus-Driven Study

H Liu
Studies in English Language Teaching
Second Language Acquisition and Learning
article

Acquisition of Valency Patterns of English Cognitive Attitude Verbs by Chinese EFL Learners: A Corpus-Driven Study

H Liu
article en

Abstract

Valency reflects the governing ability of lexical items, detailing their syntactic and semantic relationships within sentences. Studying verb valency enhances our understanding of language use and provides insights into second language acquisition. While substantial research has been conducted on learners’ second language acquisition of English verb valency, issues remain. Most studies rely on written corpora, overlooking spoken language data. Additionally, many focus on a specific verb, which limits the analysis of learners’ acquisition patterns across a broader range. This study adopts the SWECCL (Version 2.0) as the observation corpus and the BNC as the reference corpus to explore valency patterns of think, believe, consider, and prefer among Chinese ELF learners in both spoken and written corpora. Results show that Chinese learners exhibit distinct valency preferences compared to L1 speakers, resulting in overuse, underuse, and misuse. Notably, they often place animate subjects before think and believe, a pattern not observed in L1 speakers. These differences arise from second language exposure, mother tongue transfer, and cultural difference. The findings provide a comprehensive description of verb valency patterns, aiding learners in understanding valency patterns of VCAs and minimizing errors. Additionally, these insights have significant implications for foreign language teaching, particularly in vocabulary instruction.

Studies in English Language TeachingVol. 12(4)
Jilin University (CN), Jilin Medical University (CN)
Quality Education
Openalex Percentile: Top 72%
Second Language Acquisition and Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.