A Corpus-based Analysis of Lexical Richness in EAP Texts Written by Iranian TEFL Students

Masoud Azadnia
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引用次数: 1

Abstract

The literature on second/foreign language (L2/FL) discourse is replete with corpus-based studies into the use of various features representing lexical proficiency. Nonetheless, the lexical construct of English for academic purposes (EAP) texts developed by postgraduates majoring in teaching English as a foreign language (TEFL) still sounds like a relatively unexplored domain that merits further multi-dimensional investigation. To narrow the gap, the authors in the current study set out to evaluate the lexical richness of a corpus containing doctoral dissertations written by Iranian TEFL students in terms of lexical density, diversity, and sophistication. Taking advantage of the computational tool Coh-Metrix to analyze the lexical features, the corpus was analyzed in comparison with a first language (L1) baseline containing doctoral dissertations written by English native speakers. The comparative analysis of the L1 and L2 corpora revealed that the texts written by Iranian TEFL learners were lexically less diverse but more sophisticated. Additionally, the lexical density of the L2 corpus exceeded that of the L1 one in terms of nouns and adjectives. Based on the results drawn from a discriminant function analysis (DFA), the features representing lexical sophistication and density were found to be the best predictors of lexical richness since they could significantly discriminate between the two sub-corpora. The findings may provide new insights into the ways of evaluating and enhancing the lexical richness of FL/L2 written discourse.
基于语料库的伊朗TEFL学生EAP语篇词汇丰富度分析
关于第二语言/外语(L2/FL)语篇的文献中充满了基于语料库的关于词汇熟练程度的各种特征使用的研究。然而,由英语教学专业研究生开发的学术英语文本的词汇结构听起来仍然是一个相对未开发的领域,值得进一步的多维研究。为了缩小差距,本研究的作者开始从词汇密度、多样性和复杂性方面评估包含伊朗TEFL学生博士论文的语料库的词汇丰富性。利用计算工具Coh-Metrix分析词汇特征,将语料库与包含英语母语者撰写的博士论文的第一语言(L1)基线进行比较。通过对母语和第二语言语料库的对比分析发现,伊朗TEFL学习者所写的文本词汇多样性较低,但更为复杂。此外,在名词和形容词方面,第二语言语料库的词汇密度高于第一语言语料库。根据判别函数分析(DFA)的结果,表征词汇复杂性和密度的特征是词汇丰富度的最佳预测因子,因为它们可以显著区分两个子语料库。本研究结果为评价和提高二语书面语篇词汇丰富性提供了新的思路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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