世界英语:

Olesya A. Yarullina, Fanuza H. Tarasova, Elena V. Varlamova, Olga S. Safonkina, Elena V. Sazhyna
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引用次数: 0

摘要

下面的研究旨在突出文本复杂性研究的新方向,为该领域更先进、更多样化的研究让路。主要评估教学语篇的复杂性已成为俄罗斯语言学和外国语言学的传统,从而使学习者能够提高语篇理解能力和更好的材料识别能力[1],[2],[3],[4]。文本复杂性研究可以针对其他类型的文本(小说或报纸文章),以提高一般的意识水平和阅读欲望。记住,英语报纸文章可以由母语人士和非母语人士撰写,两种类型的报纸都可以用于教育目的,因此我们认为,迫切需要区分地道英语和俄语英语报纸文本的特征。即将进行的研究的研究问题可以完成如下:英语为ELF的俄罗斯人所写的英文报纸是否与真实出版物的文本具有可比性?本研究的结果将对俄语版英语作为世界英语的一部分进行研究,以证明英语变体之间的差异是否显著。为此,可以使用两种计算语言分析工具:Coh-Metrix,一种生成语言和话语表示索引的计算工具(由Arthur C. Graesser和Danielle McNamara开发),以及由宾夕法尼亚州立大学的Lu Xiaofei开发的L2句法复杂性分析器(L2SCA)(一种生成书面英语语言文本句法复杂性索引的计算工具)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WORLD ENGLISHES:
The following study aims at highlighting new directions of text complexity studies, giving way to more advanced and varied research in the area. It has become the tradition in Russian linguistics as well as foreign one to assess predominantly the complexity of educational texts, thus allowing the learners to boost text comprehension and better material recognition [1], [2], [3], [4]. Text complexity studies can be directed at other types of texts (fiction or newspaper articles) in order to raise the level of awareness and desire to read in general. Bearing in mind that newspaper articles in English can be written by native and non-native speakers, and both types of newspapers can be used in educational purposes, there is urgent need, as we perceive it, to distinguish the features of authentic and Russian English newspaper texts. The research question of upcoming studies can be accomplished as follows: Are English-language newspapers written by Russian speakers of English as ELF comparable with the texts of authentic publications? The results of this study will be interesting in terms of studying the Russian version of the English language as one of the World Englishes in order to demonstrate whether the differences between the English variants are significant. For this purpose, two tools of computational linguistic analysis can be applied: Coh-Metrix, a computational tool that produces indices of the linguistic and discourse representations (developed by Arthur C. Graesser and Danielle McNamara), and L2 Syntactical Complexity Analyzer (L2SCA) developed by Xiaofei Lu at Pennsylvania State University (a computational tool which produces syntactic complexity indices of written English language texts).
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