Studying children's writing development with a corpus

Philip Durrant
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引用次数: 1

Abstract

One of Randi Reppen's major contributions has been her pioneering corpus research into school children's writing. In this paper, I will discuss how such research can contribute to both theory and educational practice. I will then look at two sets of unresolved methodological issues in this area: the issue of defining appropriate linguistic and textual categories, and the issue of drawing valid developmental inferences.

The issue of categories arises because corpus analysis depends on abstracting away from specific instances of language use in specific texts to make claims about the use of linguistic categories (e.g., noun phrases, low-frequency vocabulary) in textual categories (e.g., stories, science reports). Such abstraction enables researchers to draw out patterns of language variation that are difficult to spot by other means. But it also raises the problem of how to define categories that are reliably operationalizable, that capture consistent developmental patterns, and that are theoretically and educationally informative.

The issue of drawing valid inferences stems from the fact that corpus data record the products of complex, contextually contingent writing processes, involving the interaction of many variables. Capturing the combined outcomes of these complex processes promotes ecological validity. However, it also creates challenges for researchers who want to draw conclusions about specific aspects of the writing process, such as writers’ knowledge of vocabulary or grammar, or their emerging awareness of audience.

This paper will discuss these issues in detail, illustrating their impact and suggesting ways forward for educationally informative corpus research.

用语料库研究儿童的写作发展
Randi Reppen的主要贡献之一是她对学校儿童写作的开创性语料库研究。在本文中,我将讨论这些研究如何对理论和教育实践做出贡献。然后,我将研究这一领域中两组尚未解决的方法论问题:定义适当的语言和文本类别的问题,以及得出有效的发展推论的问题。类别的问题之所以出现,是因为语料库分析依赖于从特定文本中语言使用的特定实例中抽象出来,从而对文本类别(如故事、科学报告)中语言类别(如名词短语、低频词汇)的使用提出要求。这种抽象使研究人员能够绘制出难以用其他方法发现的语言变化模式。但它也提出了一个问题,即如何定义可可靠地操作的类别,捕捉一致的发展模式,并在理论上和教育上提供信息。绘制有效推论的问题源于语料库数据记录了复杂的、上下文偶然的写作过程的产物,涉及许多变量的相互作用。捕获这些复杂过程的综合结果可以促进生态有效性。然而,这也给研究人员带来了挑战,他们想要得出关于写作过程的具体方面的结论,比如作家的词汇或语法知识,或者他们对读者的新兴意识。本文将详细讨论这些问题,说明它们的影响,并提出教育信息语料库研究的方向。
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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来源期刊
Applied Corpus Linguistics
Applied Corpus Linguistics Linguistics and Language
CiteScore
1.30
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70 days
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