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How word decoding, vocabulary and prior topic knowledge predict reading comprehension. A study of language-minority students in Norwegian fifth grade classrooms

机译:单词解码,词汇和先验主题知识如何预测阅读理解。挪威五年级教室中的少数民族语言学生研究

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This study examined the contribution of word decoding, first-language (L1) and second-language (L2) vocabulary and prior topic knowledge to L2 reading comprehension. For measuring reading comprehension we employed two different reading tasks: Woodcock Passage Comprehension and a researcher-developed content-area reading assignment (the Global Warming Test) consisting of multiple lengthy texts. The sample included 67 language-minority students (native Urdu or native Turkish speakers) from 21 different fifth grade classrooms in Norway. Multiple regression analyses revealed that word decoding and different facets of L2 vocabulary explained most of the variance in Woodcock Passage Comprehension, but a smaller proportion of variance in the Global Warming Test. For the Global Warming Test, prior topic knowledge was the most influential predictor. Furthermore, L2 vocabulary depth appeared to moderate the contribution of prior topic knowledge to the Global Warming Test in this sample of language minority students.
机译:这项研究检查了单词解码,第一语言(L1)和第二语言(L2)词汇以及在先主题知识对第二语言阅读理解的贡献。为了衡量阅读理解力,我们采用了两种不同的阅读任务:Woodcock Passage理解力和研究人员开发的由多个冗长的文本组成的内容区域阅读任务(全球变暖测试)。样本包括来自挪威21个不同的五年级教室的67名少数民族语言的学生(母语为乌尔都语或土耳其语)。多元回归分析显示,单词解码和L2词汇的不同方面解释了Woodcock Passage理解中的大部分差异,但全球变暖测试中的差异较小。对于全球变暖测试,先前的主题知识是最有影响力的预测因素。此外,在该语言少数族裔样本中,L2词汇深度似乎减轻了先验主题知识对全球变暖测试的贡献。

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