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首页> 外文期刊>International journal of distance education technologies >A Comparative Study on Various Vocabulary Knowledge Scales for Predicting Vocabulary Pre-Knowledge
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A Comparative Study on Various Vocabulary Knowledge Scales for Predicting Vocabulary Pre-Knowledge

机译：预测词汇预知识的各种词汇知识量表的比较研究

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摘要

The world has encountered and witnessed the great popularity of various emerging e-learning resources such as massive open online courses (MOOCs), textbooks and videos with the development of the big data era. It is critical to understand the characteristics of users to assist them to find desired and relevant learning resources in such a large volume of resources. For example, understanding the pre-knowledge on vocabulary of learners is very prominent and useful for language learning systems. The language learning effectiveness can be significantly improved if the pre-knowledge levels of learners on vocabulary can be accurately predicted. In this research, the authors model the vocabulary of learners by extracting their history of learning documents and identify the suitable vocabulary knowledge scales (VKS) for pre-knowledge prediction. The experimental results on real participants verify that the optimal VKS and the proposed predicting model are powerful and effective.
机译：随着大数据时代的发展，全世界已经遇到并见证了各种新兴的电子学习资源的广泛普及，例如大规模开放式在线课程（MOOC），教科书和视频。了解用户的特征以帮助他们在如此大量的资源中找到所需的和相关的学习资源至关重要。例如，了解学习者的词汇前知识非常重要，对于语言学习系统很有用。如果可以准确地预测词汇学习者的预知水平，则可以大大提高语言学习的效率。在这项研究中，作者通过提取学习者的学习历史来对学习者的词汇进行建模，并确定用于知识预知的合适词汇知识量表（VKS）。在真实参与者上的实验结果证明，最佳VKS和所提出的预测模型是有效的。

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