• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>Frontiers in Psychology >Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers
【2h】

Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers

机译：为文本阅读流利度中的个体差异建模：典型的发展中阅读者和阅读障碍者的预测器模式不同

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This study was aimed at predicting individual differences in text reading fluency. The basic proposal included two factors, i.e., the ability to decode letter strings (measured by discrete pseudo-word reading) and integration of the various sub-components involved in reading (measured by Rapid Automatized Naming, RAN). Subsequently, a third factor was added to the model, i.e., naming of discrete digits. In order to use homogeneous measures, all contributing variables considered the entire processing of the item, including pronunciation time. The model, which was based on commonality analysis, was applied to data from a group of 43 typically developing readers (11- to 13-year-olds) and a group of 25 chronologically matched dyslexic children. In typically developing readers, both orthographic decoding and integration of reading sub-components contributed significantly to the overall prediction of text reading fluency. The model prediction was higher (from ca. 37 to 52% of the explained variance) when we included the naming of discrete digits variable, which had a suppressive effect on pseudo-word reading. In the dyslexic readers, the variance explained by the two-factor model was high (69%) and did not change when the third factor was added. The lack of a suppression effect was likely due to the prominent individual differences in poor orthographic decoding of the dyslexic children. Analyses on data from both groups of children were replicated by using patches of colors as stimuli (both in the RAN task and in the discrete naming task) obtaining similar results. We conclude that it is possible to predict much of the variance in text-reading fluency using basic processes, such as orthographic decoding and integration of reading sub-components, even without taking into consideration higher-order linguistic factors such as lexical, semantic and contextual abilities. The approach validity of using proximal vs. distal causes to predict reading fluency is discussed.
机译：这项研究旨在预测文本阅读流畅度的个体差异。基本提议包括两个因素，即，对字母字符串进行解码的能力（通过离散伪单词读取来衡量）和读取所涉及的各个子组件的集成（通过快速自动命名（RAN）来衡量）。随后，将第三个因素添加到模型中，即，离散数字的命名。为了使用同类测度，所有影响变量都考虑了项目的整个处理过程，包括发音时间。该模型基于共性分析，被应用于来自43个典型的正在发展中的读者（11至13岁）和25个按时间顺序排列的阅读困难儿童的数据。在通常开发的阅读器中，正交解码和阅读子组件的集成都对文本阅读流畅度的总体预测做出了重要贡献。当我们包括离散数字变量的命名时，模型预测更高（从所解释方差的大约37％到52％），这对伪单词阅读产生了抑制作用。在阅读障碍的读者中，由两因素模型解释的方差很高（69％），并且在添加第三个因素时没有变化。缺乏抑制作用的原因很可能是由于阅读障碍儿童的正字法解码效果差而引起的个体差异。通过使用颜色斑块作为刺激（在RAN任务和离散命名任务中）均对两组儿童的数据进行了重复分析，获得了相似的结果。我们得出的结论是，即使不考虑词法，语义和上下文等高级语言因素，也可以使用基本过程（如正交解码和阅读子组件的集成）来预测文本阅读流利性的大部分差异。能力。讨论了使用近端原因与远端原因来预测阅读流畅度的方法有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号