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Contributions of reader- and text-level characteristics to eye-movement patterns during passage reading

机译:段落阅读过程中读者和文本水平特征对眼动模式的贡献

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摘要

The present research presents a novel method for investigating how characteristics of texts (words, sentences and passages) and individuals (verbal and general cognitive skills) jointly influence eye-movement patterns over the time-course of reading, as well as comprehension accuracy. Fifty-one proficient readers read passages of varying complexity from the Gray Oral Reading Test, while their eye-movements were recorded. Participants also completed a large battery of tests assessing various components of reading comprehension ability (vocabulary size, decoding, phonological awareness, and experience with print), as well as general cognitive and executive skills. We used the Random Forests non-parametric regression technique to simultaneously estimate relative importance of all predictors. This method enabled us to trace the temporal engagement of individual predictors and entire predictor groups on eye-movements during reading, while avoiding the problems of model overfitting and collinearity, typical of parametric regression methods. Our findings both confirmed well-established results of prior research and pointed to a space of hypotheses that is as yet unexplored.
机译:本研究提出了一种新颖的方法,用于研究文本(单词,句子和段落)和个人(语言和一般认知技能)的特征如何共同影响阅读过程中的眼动模式以及理解准确性。 51名熟练的读者从“灰色口头阅读测试”中读取了各种复杂程度不同的文章,并记录了他们的眼动。参与者还完成了大量测试,评估阅读理解能力的各个组成部分(词汇量,解码,语音意识和印刷经验)以及一般的认知和执行技能。我们使用随机森林非参数回归技术来同时估计所有预测变量的相对重要性。这种方法使我们能够追踪阅读过程中眼球运动中各个预测变量和整个预测变量组的时间参与,同时避免了模型回归和典型参数回归方法的共线性问题。我们的发现既证实了先前研究的良好结果,又指出了尚未探索的假设空间。

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