评价者在同行评价者中的错误:应用多面Rasch测量模型

R. Esfandiari
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引用次数: 6

摘要

在这项研究中,研究者使用多面拉赫测量模型(MFRM)来检测同行评估员对英语作文评分时普遍存在的两种评分错误。研究者还将同行评价者的评分与教师评价者的评分进行了比较,以更清楚地了解同行评价者的评分。为此,研究人员采用了一种完全交叉的设计,在这种设计中,所有的同行评估员都对伊朗两所私立大学的两个高级写作班的硕士学生所写的所有论文进行了评分。同行评估师使用6分分析评级量表对15项评估标准进行评估。facet分析结果表明,同行评价者作为一个群体,不存在集中趋势效应和光环效应;然而,个别同行评价者表现出不同程度的集中趋势效应和光环效应。此外,同行评价者的评分与教师评价者的评分无统计学差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rater Errors among Peer-Assessors: Applying the Many-Facet Rasch Measurement Model
In this study, the researcher used the many-facet Rasch measurement model (MFRM) to detect two pervasive rater errors among peer-assessors rating EFL essays. The researcher also compared the ratings of peer-assessors to those of teacher assessors to gain a clearer understanding of the ratings of peer-assessors. To that end, the researcher used a fully crossed design in which all peer-assessors rated all the essays MA students enrolled in two Advanced Writing classes in two private universities in Iran wrote. The peer-assessors used a 6-point analytic rating scale to evaluate the essays on 15 assessment criteria. The results of Facets analyses showed that, as a group, peer-assessors did not show central tendency effect and halo effect; however, individual peer-assessors showed varying degrees of central tendency effect and halo effect. Further, the ratings of peer-assessors and those of teacher assessors were not statistically significantly different.
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