应用语言学研究文章中的统计使用水平:从1986年到2015年

IF 0.7 2区 文学 0 LANGUAGE & LINGUISTICS Journal of Quantitative Linguistics Pub Date : 2019-01-02 DOI:10.1080/09296174.2017.1421498
Reza Khany, Khalil Tazik
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引用次数: 18

摘要

摘要本研究的主要目的是评估过去三十年(1986年至2015年)应用语言学研究文章的统计使用水平(基础、中级和高级)。该语料库包括4079项定量和混合方法研究,发表在十本著名的应用语言学杂志上。两位现任作者和四位TEFL博士生对这些文章进行了分析,并汇总了所使用的统计技术。结果显示,描述性统计(40.04%)是迄今为止最常用的技术,其次是单因素方差分析(14.91%)、t检验(10.15%)和皮尔逊相关(8.76%)。就统计使用的复杂程度而言,约78.77%(n=4686)的技术被归类为基本技术,14.49%(n=862)的技术为中级技术,6.74%(n=401)的技术属于高级技术。显然,大多数技术要么是基础技术,要么是中级技术,前者的比例要高得多。因此,一个具有统计学基础知识的人可以理解1986年至2015年发表的69.03%的论文。有人讨论说,如果研究人员希望从统计学上理解应用语言学期刊上发表的研究文章,他们应该了解最新的统计学知识。
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Levels of Statistical Use in Applied Linguistics Research Articles: From 1986 to 2015
Abstract The main objective of this study is to assess the levels of statistical use (basic, intermediate, and advanced) in Applied Linguistics research articles over the past three decades (from 1986 to 2015). The corpus included 4079 quantitative and mixed-methods studies published in ten prominent journals of Applied Linguistics. The articles were analysed and the statistical techniques used were aggregated by two current writers and four PhD students in TEFL. Results showed that descriptive statistics (40.04%) were by far the most commonly used technique followed by one-way ANOVA (14.91%), t-test (10.15%), and Pearson correlation (8.76%). Regarding the sophistication level of statistical use, about 78.77% (n = 4686) of the techniques were classified as basic, 14.49% (n = 862) as intermediate, and 6.74% (n = 401) as advanced. Clearly, most of the techniques were either basic or intermediate, with a significant higher percentage for the former. So, a person with basic knowledge of statistics could understand 69.03% of the papers published during 1986 to 2015. It is discussed that researchers should be updated on recent statistical knowledge if they wish to statistically comprehend research articles published in Applied Linguistics journals.
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来源期刊
CiteScore
2.90
自引率
7.10%
发文量
7
期刊介绍: The Journal of Quantitative Linguistics is an international forum for the publication and discussion of research on the quantitative characteristics of language and text in an exact mathematical form. This approach, which is of growing interest, opens up important and exciting theoretical perspectives, as well as solutions for a wide range of practical problems such as machine learning or statistical parsing, by introducing into linguistics the methods and models of advanced scientific disciplines such as the natural sciences, economics, and psychology.
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