用于定量测量中国大学生英语写作词汇丰富度的精炼简明指数模型

IF 2.4 Q1 EDUCATION & EDUCATIONAL RESEARCH
Yang Yang, Ze Zheng
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引用次数: 0

摘要

在现有文献中,学者们提出了各种指数来衡量英语作为外语(EFL)写作的词汇丰富度(LR)。然而,目前存在着指标冗余和用法不一致的问题。本研究试图解决 "哪些指标对区分中国大学生不同年级的 EFL 写作最为敏感和有效 "这一研究问题,提出一个能够真实反映 EFL 写作词汇丰富度的精炼而简洁的指标模型。本研究从中国 EFL 学习者语料库中选取了 180 篇作文:中国学习者英语口语和写作语料库。使用词法复杂性分析器(Lexical Complexity Analyzer)、MATTR 和 Coh-Metrix 软件计算了这些作文的 28 个 LR 指数。根据变量方差的同质性,对每个指数进行单因素方差分析或韦尔奇方差分析。在确定应将哪个测量指标纳入改进模型时,采用了两个标准:一是不同年级之间的指标差异是否显著,二是方差分析的效应大小。根据方差分析的定量结果和基于文献的人为定性判断,六个 LR 量表中的六个指数被纳入了改进模型:词性密度、词性复杂度-I、动词复杂度-II、不同词数-预期序列 50、校正 TTR 和动词变异平方-I。该改进模型解决了以往研究中存在的冗余和不一致问题,为评估 EFL 写作中的词汇量提供了一个更准确、更有效的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A refined and concise model of indices for quantitatively measuring lexical richness of Chinese university students’ EFL writing
In the existing literature, scholars have proposed various indices to measure the lexical richness (LR) of English as a foreign language (EFL) writing. However, there are currently issues of redundant indices and inconsistent usage. Attempting to address the research question of which indices are the most sensitive and effective ones to distinguish between different grade levels of Chinese university students’ EFL writing, this study aims to put forward a refined and concise model of indices that can truthfully reflect LR in EFL writing. A total of 180 compositions were selected from a Chinese EFL learner corpus: Spoken and written English corpus of Chinese learners. Scores of 28 LR indices of these compositions were computed using the software Lexical Complexity Analyzer, MATTR, and Coh-Metrix. One-way ANOVA or Welch’s ANOVA, depending on the variable’s homogeneity of variances, was conducted for each index. Two criteria were applied to determine which index of a measure should be included in the refined model: whether the difference of an index is significant among different grade levels and the effect size of ANOVA. Based on the quantitative results of ANOVAs and qualitative human judgment based on literature, six indices of the six LR measures were included in the refined model: lexical density, lexical sophistication-I, verb sophistication-II, number of different words-expected sequence 50, corrected TTR, and squared verb variation-I. This refined model addresses the issues of redundancy and inconsistency in previous studies, providing a more accurate and efficient tool for assessing LR in EFL writing.
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来源期刊
Contemporary Educational Technology
Contemporary Educational Technology Social Sciences-Education
CiteScore
6.20
自引率
0.00%
发文量
55
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