Sociocognitive and Argumentation Perspectives on Psychometric Modeling in Educational Assessment

IF 2.9 2区 心理学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Psychometrika Pub Date : 2024-04-03 DOI:10.1007/s11336-024-09966-5
Robert J. Mislevy
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Abstract

Rapid advances in psychology and technology open opportunities and present challenges beyond familiar forms of educational assessment and measurement. Viewing assessment through the perspectives of complex adaptive sociocognitive systems and argumentation helps us extend the concepts and methods of educational measurement to new forms of assessment, such as those involving interaction in simulation environments and automated evaluation of performances. I summarize key ideas for doing so and point to the roles of measurement models and their relation to sociocognitive systems and assessment arguments. A game-based learning assessment SimCityEDU: Pollution Challenge! is used to illustrate ideas.

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从社会认知和论证角度看教育评估中的心理测量建模
心理学和技术的飞速发展为我们带来了机遇和挑战,超越了我们熟悉的教育评估和测量形式。从复杂的适应性社会认知系统和论证的角度来看待评估,有助于我们将教育测量的概念和方法扩展到新的评估形式,如涉及模拟环境中的互动和对表现的自动评估。我总结了这样做的主要思路,并指出了测量模型的作用及其与社会认知系统和评估论证的关系。我将使用基于游戏的学习评估《模拟城市教育大学:污染挑战!》来说明这些观点。
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来源期刊
Psychometrika
Psychometrika 数学-数学跨学科应用
CiteScore
4.40
自引率
10.00%
发文量
72
审稿时长
>12 weeks
期刊介绍: The journal Psychometrika is devoted to the advancement of theory and methodology for behavioral data in psychology, education and the social and behavioral sciences generally. Its coverage is offered in two sections: Theory and Methods (T& M), and Application Reviews and Case Studies (ARCS). T&M articles present original research and reviews on the development of quantitative models, statistical methods, and mathematical techniques for evaluating data from psychology, the social and behavioral sciences and related fields. Application Reviews can be integrative, drawing together disparate methodologies for applications, or comparative and evaluative, discussing advantages and disadvantages of one or more methodologies in applications. Case Studies highlight methodology that deepens understanding of substantive phenomena through more informative data analysis, or more elegant data description.
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