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Combining technology and IRT testing to build student knowledge of high frequency vocabulary

机译:结合技术和IRT测试以建立学生的高频词汇知识

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This article describes a suite of free software programs for cell phones and PCs that have been created to efficiently develop ESL and EFL learner's knowledge of high frequency vocabular y. Until now, this level of efficiency has not been p ossible due to the variable nature of vocabulary knowledge within a class of students and the lack of diagnostic tools for identifying individual students' known and unknown vocabulary. The programs are capable of accurately and efficiently assessing the learner 's English lexical size, identifying which specific high frequency words still need to be taught , and then teaching these important words via a time-intervalled flashcard system and learning games focused on developing automaticity of word knowledge. Although there have been several tests available for making estimates of a learner's vocabulary profile such as Nation's Vocabulary Levels Test (1990) and Meara's Yes/No test (1992), there has been no attempts to identify the specific words a learner knows. Through the application of Item Resp onse Theory to test item resp onses, we have been able to assign perceived word difficulties to a list of the most common words in English. A computer adaptive test drawing from an item bank of these words quickly and accurately assesses the number of English words known by learners, as well as determines which specific words are known and unknown.
机译:本文介绍了一套用于手机和PC的免费软件程序,这些程序是为有效地开发ESL和EFL学习者对高频语音的知识而创建的。到目前为止,由于一类学生的词汇知识的可变性以及缺乏用于识别单个学生的已知和未知词汇的诊断工具,因此这种效率水平尚不可行。这些程序能够准确,有效地评估学习者的英语词汇量,确定仍然需要教哪些具体的高频单词,然后通过时间间隔的抽认卡系统教这些重要单词,并着重于开发自动学习能力的游戏。单词知识。尽管有几种测试方法可以估算学习者的词汇量,例如Nation的词汇水平测试(1990)和Meara的Yes / No测试(1992),但并未尝试识别学习者知道的特定单词。通过使用项目响应理论来测试项目响应,我们已经能够将感知到的单词困难分配给英语中最常见的单词列表。来自这些单词的项目库的计算机自适应测试图可快速,准确地评估学习者已知的英语单词的数量,并确定哪些特定单词已知和未知。

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