词汇表生成器:一个数字工具,用于生成基于频率的单词表,并根据分散情况进行调整

Ashleigh Cox , Daniel Dixon , Tülay Dixon
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引用次数: 0

摘要

在第二语言和外语教学中,帮助学生学习新词汇是一个重要的目标,许多研究人员旨在通过预测特定学习者群体可能需要的词汇来帮助教师确定哪些词汇应该优先使用。这种预测可以通过检查语料库中经常出现的单词来实现,这些单词代表了学习者的目标语言使用领域。早期的词汇表在对一个领域的重要词汇进行排序时,倾向于只考虑频率和范围,最近,研究人员提出了更强大的分散指标,包括均匀度(即一个词在文本中传播的均匀程度)和普遍性(即使用一个词的文本比例,类似于范围)(Egbert &;伯奇,2023)。然而,目前常用的构建基于语料库的词汇表的工具和方法往往不包括这些离散度量,尤其是均匀度量。为了使研究人员和教师更容易地通过考虑频率和推荐分散度量的词汇表来告知语言学习目标,本报告描述并演示了一种新的数字工具——词汇表生成器。该工具在心理学期刊文章的语料库中进行了试验,从语料库中生成的词汇表展示了它的使用和输出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vocabulary list generator: A digital tool to generate frequency-based word lists adjusted for dispersion
In second and foreign language teaching, helping students learn new vocabulary is an important goal, and many researchers aim to help teachers determine which vocabulary items should be prioritized by making predictions about the words that specific learner populations are likely to need. Such predictions can be made by examining the words that frequently appear in corpora that are representative of the learners’ target language use domains. While early vocabulary lists tended to consider only frequency and range when ranking important words in a domain, more recently, researchers have argued for more robust measures of dispersion, including evenness (i.e., how evenly spread a word is across texts) and pervasiveness (i.e., the proportion of texts using a word, which is similar to range) (Egbert & Burch, 2023). However, the current tools and methods that are commonly used to form corpus-based vocabulary lists often do not include these dispersion measures, especially the measure of evenness. To make it easier for researchers and teachers to inform language learning goals with vocabulary lists that consider both frequency and recommended dispersion measures, this report describes and demonstrates a new digital tool, the Vocabulary List Generator. The tool was piloted with a corpus of psychology journal articles, and the vocabulary list generated from the corpus demonstrates its use and output.
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来源期刊
CiteScore
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