Department of Psychology, University of Iowa, Iowa City, IA 52242, USA.
Philos Trans R Soc Lond B Biol Sci. 2009 Dec 27;364(1536):3755-71. doi: 10.1098/rstb.2009.0132.
Word learning is studied in a multitude of ways, and it is often not clear what the relationship is between different phenomena. In this article, we begin by outlining a very simple functional framework that despite its simplicity can serve as a useful organizing scheme for thinking about various types of studies of word learning. We then review a number of themes that in recent years have emerged as important topics in the study of word learning, and relate them to the functional framework, noting nevertheless that these topics have tended to be somewhat separate areas of study. In the third part of the article, we describe a recent computational model and discuss how it offers a framework that can integrate and relate these various topics in word learning to each other. We conclude that issues that have typically been studied as separate topics can perhaps more fruitfully be thought of as closely integrated, with the present framework offering several suggestions about the nature of such integration.
词汇学习有多种研究方法，不同现象之间的关系往往并不清楚。在本文中，我们首先概述了一个非常简单的功能框架，尽管它很简单，但可以作为思考各种词汇学习研究类型的有用组织方案。然后，我们回顾了近年来在词汇学习研究中出现的一些重要主题，并将它们与功能框架联系起来，不过需要注意的是，这些主题往往是相对独立的研究领域。在文章的第三部分，我们描述了一个最近的计算模型，并讨论了它如何提供一个框架，可以将词汇学习中的这些不同主题相互集成和联系起来。我们得出的结论是，通常作为单独主题进行研究的问题，可以更有效地被视为紧密结合的，而当前的框架则提供了关于这种结合的本质的一些建议。
