论文标题
采用分销语义来组织以任务为重点的词汇学习
Employing distributional semantics to organize task-focused vocabulary learning
论文作者
论文摘要
学习者如何系统地准备阅读他们感兴趣的书？在本文中，我们探讨了如何将计算语言学方法（例如分布语义，形态聚类和运动产生）与基于图的学习者模型相结合，以在概念上和实践中回答这个问题。根据高度结构化的学习者模型和网络分析的概念，学习者被指导以有效地探索目标的词汇空间。他们使用从本书中产生的多间隙学习活动进行练习，这些活动集中在目标词汇空间核心的单词上。因此，该方法提供了计算语言方法与网络分析和辅导系统领域的概念的独特组合，以支持学习者实现其个人，阅读基于任务的学习目标。
How can a learner systematically prepare for reading a book they are interested in? In this paper,we explore how computational linguistic methods such as distributional semantics, morphological clustering, and exercise generation can be combined with graph-based learner models to answer this question both conceptually and in practice. Based on the highly structured learner model and concepts from network analysis, the learner is guided to efficiently explore the targeted lexical space. They practice using multi-gap learning activities generated from the book focused on words that are central to the targeted lexical space. As such the approach offers a unique combination of computational linguistic methods with concepts from network analysis and the tutoring system domain to support learners in achieving their individual, reading task-based learning goals.
