A computational model associating learning process, word attributes, and age of acquisition.

A computational model associating learning process, word attributes, and age of acquisition.
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DOI:
10.1371/journal.pone.0076242
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发表时间:
2013
期刊:
影响因子:
3.7
通讯作者:
Hidaka S
Hidaka S
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Hidaka S

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我们提出了一种新的基于模型的方法,将单词学习与单词习得年龄(AoA)联系起来;一种新的计算工具,用于理解单词学习过程、心理属性和单词AoAs之间的关系,作为词汇增长的衡量标准。所开发的计算模型描述了支撑单词学习和AoA分布的三个理论因素之间独特的统计关系。简而言之,该模型阐述了不同的学习过程(以学习速率随时间的变化和/或获取单词所需的暴露次数为特征)如何可能导致不同的AoA分布(取决于单词类型)。我们从三个方面检验了这个模型。第一个分析表明,所提出的模型比标准替代模型更能说明经验的AoA分布。第二个分析表明,估计的学习参数很好地预测了词汇的心理属性,如频率和可想象性。第三个分析表明,我们估计的学习参数预测的发展趋势与儿童单词学习发展文献的相关发现是一致的。我们进一步讨论了基于模型的方法的理论含义。
We propose a new model-based approach linking word learning to the age of acquisition (AoA) of words; a new computational tool for understanding the relationships among word learning processes, psychological attributes, and word AoAs as measures of vocabulary growth. The computational model developed describes the distinct statistical relationships between three theoretical factors underpinning word learning and AoA distributions. Simply put, this model formulates how different learning processes, characterized by change in learning rate over time and/or by the number of exposures required to acquire a word, likely result in different AoA distributions depending on word type. We tested the model in three respects. The first analysis showed that the proposed model accounts for empirical AoA distributions better than a standard alternative. The second analysis demonstrated that the estimated learning parameters well predicted the psychological attributes, such as frequency and imageability, of words. The third analysis illustrated that the developmental trend predicted by our estimated learning parameters was consistent with relevant findings in the developmental literature on word learning in children. We further discuss the theoretical implications of our model-based approach.
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