Dependency distance reflects L2 processing difficulty: Evidence from the relationship between dependency distance, L2 processing speed, and L2 proficiency

Author:

Gao Jianmin1ORCID,Sun Peijian Paul1ORCID

Affiliation:

1. Department of Linguistics, Zhejiang University, China

Abstract

Aims and objectives: This study aims to investigate whether dependency distance (DD) can reflect L2 processing difficulty by exploring the relationship between DD, L2 processing speed, and L2 proficiency. Methodology: The sentences in a maze task were annotated based on dependency syntax to indicate L2 processing difficulty. The maze task then was used to capture the word-level and sentence-level processing speed. The task was successfully performed by 62 Chinese learners of English, who were assigned into an intermediate-level group and an advanced-level group according to their scores on an elicited imitation task (EIT) and a vocabulary and grammar test. Data and analysis: Reaction time (RT) data of processing word-level and sentence-level items were collected from the maze task. The DD-based estimates of word-level and sentence-level processing difficulty were calculated. Generalized linear regression models (GLMs) were employed to inspect the relationship between the DD-based estimate of processing difficulty, L2 processing speed, and L2 proficiency. Findings: Our results showed that DD significantly predicted L2 processing speed at both word and sentence levels, irrespective of participants’ L2 proficiency. As DD increased, advanced learners’ word-level processing time grew significantly slower than that of intermediate learners. Originality: Using psycholinguistic experiments, the study is one of the first attempts to empirically validate the effectiveness of DD in capturing L2 processing difficulty. Significance: Our findings suggest that DD is useful in predicting L2 processing difficulty, and the extent to which learners are able to efficiently process dependencies with increasing distance can differentiate their L2 proficiency levels.

Funder

National Social Science Foundation of China

Publisher

SAGE Publications

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3