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Grammatical Templates: Improving Text Difficulty Evaluation for Language Learners

机译:语法模板:提高语言学习者的文字难度评估

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Language students are most engaged while reading texts at an appropriate difficulty level. However, existing methods of evaluating text difficulty focus mainly on vocabulary and do not prioritize grammatical features, hence they do not work well for language learners with limited knowledge of grammar. In this paper, we introduce grammatical templates, the expert-identified units of grammar that students learn from class, as an important feature of text difficulty evaluation. Experimental classification results show that grammatical template features significantly improve text difficulty prediction accuracy over baseline readability features by 7.4%. Moreover, we build a simple and human-understandable text difficulty evaluation approach with 87.7% accuracy, using only 5 grammatical template features.
机译:语言学生在以适当的难度水平阅读课文时最投入。然而,现有的评估文本难度的方法主要集中在词汇上,并且没有优先考虑语法特征,因此,它们对于语法知识有限的语言学习者来说效果不佳。在本文中,我们介绍了语法模板,即学生从课堂上学习的专家识别的语法单元,这是文本难度评估的重要功能。实验分类结果表明,语法模板特征比基线可读性特征显着提高了文本难度预测准确性7.4%。此外,我们仅使用5个语法模板功能构建了一种简单且易于理解的文本难度评估方法,其准确度为87.7%。

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