Amaury Van Parys, Vanessa De Wilde, Lieve Macken, Maribel Montero Perez
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引用次数: 0
Abstract
Given the strong influence of vocabulary knowledge on L2 learners’ text comprehension (Schmitt et al., 2011), assessing the vocabulary demands of foreign language (L2) input is a crucial challenge for both L2 educators and researchers. To do so, a well-established step for the design, selection, and empirical analysis of L2 input is to use tools for lexical profiling. This involves categorising a text’s vocabulary across levels in a word frequency list to estimate the vocabulary knowledge learners need in order to achieve satisfactory comprehension. However, current tools are mainly available for English and are built on word family-based frequency lists derived from broad corpora, which have been suggested to have more limited predictive power of learner knowledge than previously presumed (Schmitt et al., 2021). This article presents LexPro, a new plurilingual lexical profiling tool which was programmed in Python and facilitates analysis of individual texts and corpora in English, French, Spanish, and Dutch. It relies on flemmatised word frequency lists derived from subtitle corpora, on the empirical ground that these are more reflective of learner knowledge (Pinchbeck et al., 2022). Output includes general text characteristics (e.g., text length, lexical diversity), a lexical profile with accompanying visuals, an overview of the used vocabulary, and detailed insights into word repetition as well as the number of texts in which words appear. To illustrate the potential applications of the tool for both research and teaching practice, a use case is presented analysing an Intermediate French L2 textbook. The paper concludes with practical recommendations for implementing LexPro in educators’ text selection processes.
鉴于词汇知识对二语学习者文本理解的强烈影响(Schmitt et al., 2011),评估外语(L2)输入的词汇需求是二语教育者和研究者面临的一个重要挑战。要做到这一点,设计、选择和实证分析第二语言输入的一个行之有效的步骤是使用词汇分析工具。这包括在词频表中对文本的词汇进行不同级别的分类,以估计学习者为了达到满意的理解所需要的词汇知识。然而,目前的工具主要用于英语,并且是建立在来自广泛语料库的基于词族的频率列表上的,这被认为对学习者知识的预测能力比以前假设的要有限(Schmitt et al., 2021)。本文介绍了LexPro,一个新的多语种词汇分析工具,它是用Python编程的,可以方便地分析英语、法语、西班牙语和荷兰语的单个文本和语料库。它依赖于派生自字幕语料库的flemmalized词频列表,基于经验,这些列表更能反映学习者的知识(Pinchbeck et al., 2022)。输出包括一般文本特征(例如,文本长度、词汇多样性)、附带视觉效果的词汇概况、使用词汇的概述、单词重复的详细信息以及单词出现的文本数量。为了说明该工具在研究和教学实践中的潜在应用,本文提出了一个用例,分析中级法语L2教科书。论文最后提出了在教育工作者的文本选择过程中实施LexPro的实用建议。
期刊介绍:
Language Teaching Research is a peer-reviewed journal that publishes research within the area of second or foreign language teaching. Although articles are written in English, the journal welcomes studies dealing with the teaching of languages other than English as well. The journal is a venue for studies that demonstrate sound research methods and which report findings that have clear pedagogical implications. A wide range of topics in the area of language teaching is covered, including: -Programme -Syllabus -Materials design -Methodology -The teaching of specific skills and language for specific purposes Thorough investigation and research ensures this journal is: -International in focus, publishing work from countries worldwide -Interdisciplinary, encouraging work which seeks to break down barriers that have isolated language teaching professionals from others concerned with pedagogy -Innovative, seeking to stimulate new avenues of enquiry, including ''action'' research