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阅读的难解之谜。

The unexplained nature of reading.

机构信息

Department of Psychology.

Department of Marketing.

出版信息

J Exp Psychol Learn Mem Cogn. 2013 Jul;39(4):1037-1053. doi: 10.1037/a0031829. Epub 2013 Apr 8.

Abstract

The effects of properties of words on their reading aloud response times (RTs) are 1 major source of evidence about the reading process. The precision with which such RTs could potentially be predicted by word properties is critical to evaluate our understanding of reading but is often underestimated due to contamination from individual differences. We estimated this precision without such contamination individually for 4 people who each read 2,820 words 50 times each. These estimates were compared to the precision achieved by a 31-variable regression model that outperforms current cognitive models on variance-explained criteria. Most (around 2/3) of the meaningful (non-first-phoneme, non-noise) word-level variance remained unexplained by this model. Considerable empirical and theoretical-computational effort has been expended on this area of psychology, but the high level of systematic variance remaining unexplained suggests doubts regarding contemporary accounts of the details of the mechanisms of reading at the level of the word. Future assessment of models can take advantage of the availability of our precise participant-level database.

摘要

词的属性对朗读反应时(RT)的影响是阅读过程的主要证据来源之一。这些 RT 可以通过词的属性进行预测的精确程度对于评估我们对阅读的理解至关重要,但由于个体差异的干扰,这种精确程度往往被低估。我们分别对 4 个人进行了单独的估计,他们每个人都读了 2820 个单词,每个单词读 50 次。这些估计值与一个 31 变量回归模型的精度进行了比较,该模型在解释方差的标准上优于当前的认知模型。该模型仍无法解释大部分(约 2/3)有意义的(非首音、非噪声)词级方差。在这个心理学领域已经投入了大量的实证和理论计算工作,但仍有大量系统方差无法解释,这表明人们对阅读机制细节的当代解释存在疑问。未来对模型的评估可以利用我们精确的参与者层面数据库的可用性。

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