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语音构词概率和音位邻接密度的递增变化对学龄前儿童词汇学习的影响。

The effect of incremental changes in phonotactic probability and neighborhood density on word learning by preschool children.

机构信息

Correspondence to Holly L. Storkel:

出版信息

J Speech Lang Hear Res. 2013 Oct;56(5):1689-700. doi: 10.1044/1092-4388(2013/12-0245). Epub 2013 Jul 23.

Abstract

PURPOSE

Phonotactic probability or neighborhood density has predominately been defined through the use of gross distinctions (i.e., low vs. high). In the current studies, the authors examined the influence of finer changes in probability (Experiment 1) and density (Experiment 2) on word learning.

METHOD

The authors examined the full range of probability or density by sampling 5 nonwords from each of 4 quartiles. Three- and 5-year-old children received training on nonword-nonobject pairs. Learning was measured in a picture-naming task immediately following training and 1 week after training. Results were analyzed through the use of multilevel modeling.

RESULTS

A linear spline model best captured nonlinearities in phonotactic probability. Specifically, word learning improved as probability increased in the lowest quartile, worsened as probability increased in the mid-low quartile, and then remained stable and poor in the 2 highest quartiles. An ordinary linear model sufficiently described neighborhood density. Here, word learning improved as density increased across all quartiles.

CONCLUSION

Given these different patterns, phonotactic probability and neighborhood density appear to influence different word learning processes. Specifically, phonotactic probability may affect recognition that a sound sequence is an acceptable word in the language and is a novel word for the child, whereas neighborhood density may influence creation of a new representation in long-term memory.

摘要

目的

音位形态概率或音位邻域密度主要通过使用粗略区分(即低与高)来定义。在当前的研究中,作者研究了概率(实验 1)和密度(实验 2)更细微变化对单词学习的影响。

方法

作者通过从每个四分位数中抽取 5 个非单词来检查概率或密度的全范围。3 岁和 5 岁的儿童接受了关于非单词-非物体对的训练。在训练后和训练后 1 周,通过图片命名任务来测量学习情况。通过使用多层建模来分析结果。

结果

线性样条模型最好地捕捉了音位形态概率的非线性。具体来说,在最低四分位数中,随着概率的增加,单词学习得到改善,在中低四分位数中,随着概率的增加,单词学习恶化,然后在 2 个最高四分位数中保持稳定和较差。普通线性模型充分描述了音位邻域密度。在这里,随着密度在所有四分位数中增加,单词学习得到提高。

结论

鉴于这些不同的模式,音位形态概率和音位邻域密度似乎影响不同的单词学习过程。具体来说,音位形态概率可能会影响到对一个声音序列是语言中可接受的单词并且是孩子的新单词的识别,而音位邻域密度可能会影响到在长期记忆中创建新的表示。

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3
12-month-olds' phonotactic knowledge guides their word-object mappings.
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7
Adult and child semantic neighbors of the Kroll and Potter (1984) nonobjects.
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8
Developmental differences in the effects of phonological, lexical and semantic variables on word learning by infants.
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9
On the use of multilevel modeling as an alternative to items analysis in psycholinguistic research.
Behav Res Methods. 2007 Nov;39(4):723-30. doi: 10.3758/bf03192962.
10
Multilevel models for the experimental psychologist: foundations and illustrative examples.
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