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Toward Automated Multi-trait Scoring of Essays: Investigating Links among Holistic, Analytic, and Text Feature Scores

机译:实现论文的多特征自动评分:调查整体,分析和文本特征评分之间的联系

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The main purpose of the study was to investigate the distinctness and reliability of analytic (or multi-trait) rating dimensions and their relationships to holistic scores and e-rater® essay feature variables in the context of the TOEFL® computer-based test (TOEFL CBT) writing assessment. Data analyzed in the study were holistic and multi-trait essay scores provided by human raters and essay feature variable scores computed by e-rater® (version 2.0) for two TOEFL CBT writing prompts. It was found that (i) all of the six multi-trait scores were not only correlated among themselves but also correlated with the holistic score, (ii) high correlations obtained among holistic and multi-trait scores were largely attributable to the impact of essay length on both holistic and multi-trait scoring, and (iii) some strong associations were confirmed between several e-rater variables and multi-trait rating dimensions. Implications are discussed for improving the multi-trait scoring of essays, refining e-rater essay feature variables, and validating automated essay scores.
机译:这项研究的主要目的是研究基于TOEFL®计算机测试(TOEFL)的分析(或多特征)评级维度的独特性和可靠性,以及它们与整体得分和e-rater®论文特征变量之间的关系。 CBT)写作评估。该研究中分析的数据是人类评分者提供的整体性和多特征论文得分,以及e-rater®(2.0版)针对两个TOEFL CBT写作提示所计算的论文特征变量得分。结果发现:(i)六个多特征得分中的所有得分不仅彼此相关,而且与整体得分相关;(ii)整体和多特征得分之间获得的高度相关性很大程度上归因于论文的影响整体评分和多特征评分的长度,以及(iii)在几个e-rater变量和多特征评分维度之间确认了一些强关联。讨论了对提高论文多特征评分,完善电子评分者论文特征变量以及验证自动论文分数的意义。

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    《Applied Linguistics》 |2010年第3期|p.391-417|共27页
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  • 入库时间 2022-08-18 01:11:41

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