Usage-based analysis of L2 oral proficiency: <i>Characteristics of argument structure construction use</i>

Abstract Analyzing the relationship between argument structure construction (ASC) use and language learning has been an important area of investigation in second language (L2) studies from a usage-based constructionist approach. Previous studies have shown that advanced L2 learners’ language use demonstrates greater ASC diversity, less frequent ASC-verb combinations, and stronger ASC-verb associations. However, these investigations have been limited by methodological challenges in identifying ASCs and have predominantly focused on the written texts. To address these limitations, we employ a fine-tuned model to automatically extract ASCs from target and reference corpora, considering their semantic aspects. We then calculate ASC-based indices and, both alone and in combination with other lexicogrammatical indices, use them to predict L2 oral proficiency scores assigned by human judges. Our findings show that ASC-based indices alone explain 44% of the variance in scores. When combined with other indices, they provide complementary insights that enhance multivariate modeling of L2 oral proficiency.

Authors

Institutions

Publication Details

Journal
Studies in Second Language Acquisition
Published
2025-08-04
DOI
https://doi.org/10.1017/s0272263125100995
Citations
1
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
2.48

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Usage-based analysis of L2 oral proficiency: Characteristics of argument structure construction use

Kristopher Kyle, Hakyung Sung
1 citations
Studies in Second Language Acquisition
Natural Language Processing Techniques
2.48
article

Usage-based analysis of L2 oral proficiency: Characteristics of argument structure construction use

Kristopher Kyle, Hakyung Sung
article en
1 citations

Abstract

Abstract Analyzing the relationship between argument structure construction (ASC) use and language learning has been an important area of investigation in second language (L2) studies from a usage-based constructionist approach. Previous studies have shown that advanced L2 learners’ language use demonstrates greater ASC diversity, less frequent ASC-verb combinations, and stronger ASC-verb associations. However, these investigations have been limited by methodological challenges in identifying ASCs and have predominantly focused on the written texts. To address these limitations, we employ a fine-tuned model to automatically extract ASCs from target and reference corpora, considering their semantic aspects. We then calculate ASC-based indices and, both alone and in combination with other lexicogrammatical indices, use them to predict L2 oral proficiency scores assigned by human judges. Our findings show that ASC-based indices alone explain 44% of the variance in scores. When combined with other indices, they provide complementary insights that enhance multivariate modeling of L2 oral proficiency.

Studies in Second Language AcquisitionVol. 47(4)
University of Oregon (US)
Educational Testing Service
Openalex Percentile: Top 9%
Natural Language Processing Techniques
2.48
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.