The Cambridge Handbook of Learner Corpus Research: Variability in learner corpora
The Cambridge Handbook of Learner Corpus Research: Variability in learner corpora
复制标题
剑桥学习者语料库研究手册：学习者语料库的变异性
DOI：
--
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Annelie Ädel
中科院分区：
文献类型：
--
作者：
Annelie Ädel
语料库和基于语料库的方法可以为研究学习者语言的变异性做出贡献，主要有两个原因。其中一个原因是，语言变异研究本身特别适合于定量和基于语料库的分析。语料库，特别是当与有关所代表的学习者和语言产生情况的元数据结合使用时，使研究人员能够以系统的方式量化和比较数据。定量语料库的结果可以用来验证或证伪第二语言习得文献中的观点，或者产生关于学习者语言的新假设。另一个原因是，在语料库工作中关注自然发生的语言意味着所研究的学习者数据类型代表了真实的语言使用。在二语习得中有很多实验工作，这意味着被分析的语言是在实验环境（如实验室）中产生的，通常只是为了语言分析的明确目的。虽然对语言数据进行实验性的启发有很多好的理由——语言使用的复杂性降低了；语言的产生和可能影响它的变量是可以控制的；捕获相关类型的语言输出的可能性可以最大化-这也是这种数据根本不能代表真实语言使用的全部范围的情况。几乎不可避免的是，研究学习者语料库数据的研究人员会遇到语言的变化，需要对其进行解释。学习者语料库研究对母语背景对学习者语言的影响给予了大量关注（见本卷第15章），但它往往忽视了其他可能产生影响的因素，这些因素可能有助于解释学习者语料库中所证实的一些可变性。本章将讨论其中一些替代因素，并展示它们在语言生产中的重要性，特别是在外语/第二语言生产中。语言不是一种静态的现象，而是根据为什么使用它、在哪里使用它、由谁使用它等等而变化的，有时变化很大。
Corpora and corpus-based methods can make a contribution to the study of variability in learner language for two main reasons. One reason is that the study of linguistic variation itself is particularly amenable to quantitative and corpus-based analysis. The corpus, especially when used in combination with metadata about the learners represented and about the situation in which the language was produced, enables the researcher to quantify and compare data in systematic ways. The quantitative corpus results can then be used to verify or falsify claims made in the second language acquisition (SLA) literature or to generate new hypotheses about learner language. Another reason is that the focus on naturally occurring language in corpus work means that the types of learner data studied represent authentic language use. There is much experimental work in SLA, which means that the language analysed is produced in an experimental setting (such as a laboratory), typically solely for the express purpose of linguistic analysis. While there are many good reasons for the experimental elicitation of linguistic data – the complexity of language use is reduced; the language production and variables potentially affecting it can be controlled; the likelihood of capturing relevant types of linguistic output can be maximised – it is also the case that such data simply do not represent the full gamut of authentic language use. Almost inevitably, researchers who study learner corpus data will encounter linguistic variability and will need to account for it. Learner corpus research has paid a great deal of attention to the influence of the mother-tongue background on learner language (see Chapter 15, this volume), but it has tended to neglect other factors that may exert an influence and that may serve to account for some of the variability attested in learner corpora. This chapter will discuss some of these alternative factors and demonstrate how important they can be in language production in general and in foreign/second language production in particular. 2 Core issues Language is not a static phenomenon, but rather varies – sometimes considerably – depending on why it is used, where it is used, by whom it is used, and so on.