部分信用IRT模型在多重评定量表工具基准识别中的应用。

Q2 Social Sciences
Enis Dogan
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引用次数: 2

摘要

几项大规模评估包括学生、教师和学校背景调查问卷。这些问卷的结果可以单独报告每个项目,也可以将多个项目汇总成一个量表作为指标。然而,解释量表得分并不总是一件容易的事。在传播成绩测试结果时,解决这一难题的一个办法是确定报告量表上的最低分数,以便根据不同的知识和技能概况将其划分为不同的成绩水平。除了平均分数外,还可以报告每个成绩级别的学生百分比。将量表划分为有意义的部分可以,也许应该这样做,以丰富基于问卷项目的量表的可解释性。本文阐述了一种基于项目反应理论(IRT)应用的方法来实现这一目标。应用多元评等量表来衡量学生的学校归属感。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Application of the Partial Credit IRT Model in Identifying Benchmarks for Polytomous Rating Scale Instruments.
Several large scale assessments include student, teacher, and school background questionnaires. Results from such questionnaires can be reported for each item separately, or as indices based on aggregation of multiple items into a scale. Interpreting scale scores is not always an easy task though. In disseminating results of achievement tests, one solution to this conundrum is to identify cut scores on the reporting scale in order to divide it into achievement levels that correspond to distinct knowledge and skill profiles. This allows for the reporting of the percentage of students at each achievement level in addition to average scale scores. Dividing a scale into meaningful segments can, and perhaps should, be done to enrich interpretability of scales based on questionnaire items as well. This article illustrates an approach based on an application of Item Response Theory (IRT) to accomplish this. The application is demonstrated with a polytomous rating scale instrument designed to measure students’ sense of school belonging.
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CiteScore
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