漢語二語者詞匯豐富性與寫作成績的相關性——兼論測量寫作質量的多元線性回歸模型及方程
發(fā)布時間:2018-09-19 16:42
【摘要】:Read(2000)的詞匯豐富性框架被視為測量寫作質量的有效工具,本研究以該框架中的詞匯多樣性、詞匯復雜性、詞頻概貌和詞匯錯誤為觀察維度,將原有的7種因素擴展為27種。選取北京語言大學“HSK動態(tài)作文語料庫”中360篇作文為樣本,首先考察漢語二語者寫作成績與各因素的相關性;在此基礎上,檢驗現(xiàn)有框架及擴展因素對漢語二語者寫作成績的預測效度,篩選有效參項,建立寫作評價模型和回歸方程。研究表明,現(xiàn)有框架中的詞匯錯誤比重及擴展因素中的詞種數(shù)、常用詞數(shù)可作為構建模型的重要參項。
[Abstract]:Read (2000)'s lexical richness framework is regarded as an effective tool to measure the quality of writing. The present study uses the lexical diversity, lexical complexity, word frequency profile and lexical errors in the framework as the observation dimensions, and extends the original 7 factors to 27. A sample of 360 compositions from the HSK dynamic composition Corpus of Beijing language and language University was selected to investigate the correlation between the writing achievement of Chinese L2 learners and various factors. This paper examines the validity of the existing framework and extended factors in predicting Chinese L2 writing scores, selects valid parameters, and establishes a writing evaluation model and regression equation. The results show that the proportion of lexical errors in the existing framework and the number of words in the extended factors, and the number of common words can be used as important parameters to construct the model.
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本文編號:2250719
[Abstract]:Read (2000)'s lexical richness framework is regarded as an effective tool to measure the quality of writing. The present study uses the lexical diversity, lexical complexity, word frequency profile and lexical errors in the framework as the observation dimensions, and extends the original 7 factors to 27. A sample of 360 compositions from the HSK dynamic composition Corpus of Beijing language and language University was selected to investigate the correlation between the writing achievement of Chinese L2 learners and various factors. This paper examines the validity of the existing framework and extended factors in predicting Chinese L2 writing scores, selects valid parameters, and establishes a writing evaluation model and regression equation. The results show that the proportion of lexical errors in the existing framework and the number of words in the extended factors, and the number of common words can be used as important parameters to construct the model.
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本文編號:2250719
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