同译性、搭配频率和共现强度对搭配接受性知识的影响——以日语名动搭配为例
The Effects of Congruence with the First Language,Collocational Frequency,and Collocational Strength on the Acceptability Knowledge of Collocations:The Case of Japanese Noun-verb Collocations
刘瑞利1
作者信息
摘要
在二语习得中,同译性、搭配频率和共现强度对搭配的习得扮演着重要角色.探讨这些因素对搭配习得的影响,有助于为搭配教学提供针对性建议.文章采用有语境条件下的搭配可接受性判断测试,调查了这些因素对中国日语学习者名动搭配接受性知识的影响.结果显示:1)随着学习者二语能力的提升,母语对搭配接受性知识的影响逐渐减弱;2)低水平组主要受到同译性和搭配频率的影响,高水平组则受到同译性、搭配频率和共现强度的综合影响;3)无论高低水平组,汉日一致搭配的接受性知识都不受搭配频率的影响;日语独有搭配则受搭配频率的影响,高频搭配较低频搭配容易习得.基于这些发现,文章最后对中国的日语搭配教学提出了具体建议.
Abstract
The acquisition of second language(L2)collocations is influenced by factors such as congruence with the first language(L1),collocational frequency,and collocational strength.Investigating the effects of these factors on collocation acquisition can offer valuable insights for teaching collocations.This study aims to investigate how these factors affect Chinese learners'knowledge of Japanese noun-verb collocations,employing a collocation acceptability judgment test conducted under contextual conditions.The findings indicate that:(1)the influence of L1 on L2 collocation acceptability knowledge diminishes as L2 proficiency increases;(2)learners with lower proficiency levels are primarily influenced by L1 congruence and collocational frequency,while those at higher levels are influenced by L1 congruence,collocational frequency,and collocational strength;(3)regardless of proficiency level,learners find congruent collocations more easily learnable,and this ease is not affected by collocational frequency.In contrast,the acquisition of Japanese-specific collocations,influenced by their frequency,demonstrates that high-frequency collocations are more readily learned than low-frequency ones.Based on these insights,the paper offers several recommendations for teaching Japanese collocations in China.
关键词
名动搭配/同译性/搭配频率/共现强度/交互效应Key words
noun-verb collocations/L1 congruence/collocational frequency/collocational strength/interaction引用本文复制引用
基金项目
2022年度广东省哲学社会科学规划外语信息化专项项目(GD22WZX02-02)
出版年
2024
NETL
NSTL
万方数据