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自动化作为一个独立的特征,可预测中学生的阅读成绩。

Automaticity as an independent trait in predicting reading outcomes in middle-school.

机构信息

Institute of Psychology, RWTH Aachen Universit.

Department of Psychological and Brain Sciences, University of Iowa.

出版信息

Dev Psychol. 2021 Mar;57(3):361-375. doi: 10.1037/dev0001153. Epub 2021 Feb 11.

Abstract

Many middle-school students struggle with basic reading skills. One reason for this might be a lack of automaticity in word-level lexical processes. To investigate this, we used a novel backward masking paradigm, in which a written word is either covered with a mask or not. Participants (N = 444 [after exclusions]; nfemale = 264, nmale = 180) were average to struggling middle-school students from an urban area in Eastern Iowa that were all native speakers of English and were roughly equally from grades 6, 7, and 8 (average age: 13 years). Two-hundred-fifty-five students qualified for free or reduced-price lunch, a proxy for economic disadvantage. Participants completed different masked and unmasked task versions where they read a word and selected a response (e.g., a pictured referent). This was related to standardized measures of decoding, fluency, and reading comprehension. Decoding was uniquely predicted by knowledge (unmasked performance), whereas fluency was uniquely predicted by automaticity (masked performance). Automaticity was stable across two testing points. Thus, automaticity should be considered an individually reliable marker/reading trait that uniquely predicts some skills in average to struggling middle-school students. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

摘要

许多中学生在基本阅读技能方面存在困难。造成这种情况的一个原因可能是在单词层面的词汇处理上缺乏自动化。为了研究这个问题,我们使用了一种新颖的反向掩蔽范式,在这种范式中,一个书面单词要么被掩蔽,要么不被掩蔽。参与者(N=444[排除后];nfemale=264,nmale=180)是来自爱荷华州东部一个城市地区的平均到挣扎中的中学生,他们都是英语母语者,大致来自 6、7 和 8 年级(平均年龄:13 岁)。255 名学生有资格享受免费或减价午餐,这是经济劣势的一个指标。参与者完成了不同的掩蔽和非掩蔽任务版本,在这些任务中,他们阅读一个单词并选择一个答案(例如,一个图片指称)。这与解码、流畅性和阅读理解的标准化测量有关。解码仅由知识(未掩蔽的表现)预测,而流畅性仅由自动性(掩蔽的表现)预测。自动性在两个测试点之间是稳定的。因此,自动性应该被视为一个个体可靠的标记/阅读特征,它可以独特地预测平均到挣扎中的中学生的一些技能。(PsycInfo 数据库记录(c)2021 APA,保留所有权利)。

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本文引用的文献

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