一种高度适应性的PISA测试设计

IF 1.4 4区 心理学 Q3 PSYCHOLOGY, APPLIED
Andreas Frey, Christoph König, Aron Fink
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引用次数: 0

摘要

高适应性测试(HAT)设计是作为国际学生评估项目(PISA)的替代测试设计引入的。HAT的原则是在选择项目时尽可能适应,同时考虑到PISA的非统计约束和解决与PISA有关的问题,如项目位置效应。HAT结合了计算机自适应测试领域的既定方法。它是用R实现的,并提供了代码。在一项基于因子设计的模拟研究中,将HAT与PISA 2018多阶段设计(MST)进行了比较,其中自变量为反应概率(RP;.50, .62)、项目池最优性(PISA 2018,最优)和能力水平(低、中、高)。实施了关于样本量、缺失回复和非统计约束的pisa特定条件。HAT在测试信息、RMSE和跨能力组的约束管理方面明显优于MST,但是它显示出稍弱的项目暴露。将RP提高到0.62并没有减少太多的考试信息,因此是一个可行的选择,以促进学生的应试经验与HAT。当使用假设的最优项目池时,HAT的测试信息比MST高三倍。综上所述,HAT被证明是一个很有前途和适用于PISA的测试设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Highly Adaptive Testing Design for PISA
The highly adaptive testing (HAT) design is introduced as an alternative test design for the Programme for International Student Assessment (PISA). The principle of HAT is to be as adaptive as possible when selecting items while accounting for PISA's nonstatistical constraints and addressing issues concerning PISA such as item position effects. HAT combines established methods from the field of computerized adaptive testing. It is implemented in R and code is provided. HAT was compared to the PISA 2018 multistage design (MST) in a simulation study based on a factorial design with the independent variables response probability (RP; .50, .62), item pool optimality (PISA 2018, optimal), and ability level (low, medium, high). PISA-specific conditions regarding sample size, missing responses, and nonstatistical constraints were implemented. HAT clearly outperformed MST regarding test information, RMSE, and constraint management across ability groups but it showed slightly weaker item exposure. Raising RP to .62 did not decrease test information much and is therefore a viable option to foster students’ test-taking experience with HAT. Test information for HAT was up to three times higher than for MST when using a hypothetical optimal item pool. Summarizing, HAT proved to be a promising and applicable test design for PISA.
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来源期刊
CiteScore
2.30
自引率
7.70%
发文量
46
期刊介绍: The Journal of Educational Measurement (JEM) publishes original measurement research, provides reviews of measurement publications, and reports on innovative measurement applications. The topics addressed will interest those concerned with the practice of measurement in field settings, as well as be of interest to measurement theorists. In addition to presenting new contributions to measurement theory and practice, JEM also serves as a vehicle for improving educational measurement applications in a variety of settings.
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