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Microfeatures influencing writing quality: the case of Chinese students' SAT essays

机译：影响写作质量的微泡：中国学生坐在散文的案例

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摘要

This study investigates the extent to which microfeatures - such as basic text features, readability, cohesion, and lexical diversity based on specific word lists - affect Chinese EFL writing quality. Data analysis was conducted using natural language processing, correlation analysis and stepwise multiple regression analysis on a corpus of 268 Chinese students' SAT writing in response to a single prompt. The results show that word count, the number of words per sentence, the connecting word frequency, the number of commas per sentence, the stop word frequency and the Coleman-Liau readability index (CLI) contribute significantly towards predicting SAT essay scores of Chinese EFL students. The regression model explains 62.6% of the variance in predicting the SAT essay's score where the number of commas per sentence acts as a suppressor. Surprisingly, none of the word lists were found to be a significant predictor. Consequently, EFL teachers can adopt these simple lexical features to formulate writing strategies for beginner level Chinese EFL students to improve their SAT writing quality. Moreover, developers can include these features as a personalized option in automated writing assistance systems targeted toward beginner level Chinese EFL students.
机译：本研究研究了微象的程度 - 根据特定字列表的基本文本特征，可读性，凝聚力和词汇分集 - 影响中国EFL写作质量。使用自然语言处理，相关性分析和逐步多元回归分析进行数据分析，以响应单个提示，对268名中国学生坐书的卫星进行撰写。结果表明，单词数，每句话的单词数，连接字频率，每句话的逗号数，停止字频率和科学 - 廖可读性指数（CLI）有贡献，旨在预测中国EFL的SAT论文评分学生们。回归模型解释了预测SAT论文的分数的62.6％，其中每个句子的逗号数量充当抑制器。令人惊讶的是，发现这个词列表都没有发现是一个重要的预测因素。因此，EFL教师可以采用这些简单的词汇特征，以制定初学者级别的efl学生的写作策略，以提高他们的卫星写作质量。此外，开发人员可以将这些特征包括在朝向初级中国EFL学生的自动写作辅助系统中的个性化选项。

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