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Context Variation and Definitions in Learning the Meanings of Words: An Instance-Based Learning Approach

机译:学习单词含义的语境变化和定义:一种基于实例的学习方法

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This article proposes an instance-based theoretical framework to account for the influence of both contexts and definitions on learning new word meanings and reports 2 studies that examine hypotheses about learning from context. One is that variation in contexts is important for allowing core meaning features of a word to emerge. The second is that definitions are effective because they can interact with contexts to communicate core meanings. Both experiments tested the effects of context variation by presenting adult learners with context sentences that either varied or repeated with each training trial. Experiment 1 varied whether definitions were also provided, whereas Experiment 2 varied context variability without definitions and examined the role of reading comprehension skill and pre-training word familiarity. Results across several different measures were that exposure to variable contexts led to better learning of abstract meanings than did equivalent exposure to a single context. In addition, definitions were more effective at conveying this knowledge than context alone. The instance-based framework accounts for the dual effects of contexts and definitions, suggesting how word learning results from abstraction across varied word encounters, both definitions and context sentences.
机译:本文提出了一个基于实例的理论框架,以说明上下文和定义对学习新词的含义的影响,并报告了两项研究,旨在研究从上下文学习的假设。一个是,上下文的变化对于允许出现单词的核心含义特征很重要。第二个定义是有效的,因为它们可以与上下文交互以传达核心含义。这两个实验都通过向成年学习者展示每次训练试验中变化或重复的上下文句子来测试上下文变化的影响。实验1改变了是否也提供了定义,而实验2改变了没有定义的上下文可变性,并检验了阅读理解能力和预训练单词熟悉度的作用。几种不同测量方法的结果是,与同等暴露于单个上下文相比,暴露于可变上下文可以更好地学习抽象含义。此外,定义在传达这些知识方面比单独的上下文更有效。基于实例的框架考虑了上下文和定义的双重影响,提出了单词学习如何从各种单词遇到(定义和上下文句子)的抽象中得到结果。

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