Text length effects on the reliability of syntactic complexity indices

Hyun-Bin Hwang, Charlene Polio
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Abstract

Automated tools are widely used to assess syntactic complexity in second language (L2) writing studies; however, the effects of text length on syntactic complexity indices remain unclear. This can pose a challenge when studying underrepresented populations (e.g., young learners, adults with limited literacy skills), as their lower proficiency may result in less text production. To address this issue, we investigated the minimum text length threshold at which automated measures of syntactic complexity become the most reliable while considering L2 proficiency and prompt topic. Essays from the ICNALE corpus, a dataset of 5,200 essays with four proficiency levels, were used to create a dataset of texts of varying lengths (50, 100, 150, and 200 words). Mixed-effects regression models showed that seven out of 14 indices were not affected by text length regardless of learner proficiency and prompt topic. The other seven differed only between the 50- and 200-word texts within intermediate levels. We suggest a minimum of 100 words as a conservative threshold for the reliability of syntactic complexity indices. Finally, we emphasize the importance of transparent reporting practice regarding text length information.

文本长度对句法复杂度指标可靠性的影响
自动化工具被广泛用于评估第二语言(L2)写作研究中的句法复杂性;然而,语篇长度对句法复杂性指数的影响尚不清楚。在研究代表性不足的人群(例如,年轻的学习者、识字能力有限的成年人)时,这可能会带来挑战,因为他们的熟练程度较低可能会导致文本制作较少。为了解决这个问题,我们研究了在考虑二语熟练程度和提示主题的情况下,句法复杂性的自动测量成为最可靠的最小文本长度阈值。ICNALE语料库是一个由5200篇论文组成的数据集,具有四个熟练程度,用于创建不同长度(50、100、150和200个单词)的文本数据集。混合效应回归模型显示,无论学习者的熟练程度和提示主题如何,14个指标中有7个不受文本长度的影响。其他七个不同的只是在50和200字的中等水平的文本之间。我们建议至少100个单词作为句法复杂性指数可靠性的保守阈值。最后,我们强调关于文本长度信息的透明报告做法的重要性。
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