Item selection methods with exposure and time control for computerized classification test

IF 1.5 3区 心理学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Yingshi Huang, He Ren, Ping Chen
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引用次数: 0

Abstract

Computerized classification testing (CCT) commonly chooses items maximizing information at the cut score, which yields the most information for decision-making. However, a corollary problem is that all examinees will be given the same set of items, resulting in high test overlap rate and unbalanced item bank usage, which threatens test security. Moreover, another pivotal issue for CCT is time control. Since both the extremely long response time (RT) and large RT variability across examinees intensify time-induced anxiety, it is crucial to reduce the number of examinees exceeding the time limitation and the differences between examinees' test-taking times. To satisfy these practical needs, this paper proposes the novel idea of stage adaptiveness to tailor the item selection process to the decision-making requirement in each step and generate fresh insight into the existing response time selection method. Results indicate that a balanced item usage as well as short and stable test times across examinees can be achieved via the new methods.

计算机分类测验中具有曝光和时间控制的选题方法
计算机分类测试(CCT)通常选择在分值上信息最大化的项目,这为决策提供了最多的信息。然而,随之而来的一个问题是,所有考生都将被分配相同的考题,导致考试重叠率高,题库使用不平衡,威胁到考试的安全性。此外,CCT的另一个关键问题是时间控制。由于超长的反应时间和较大的反应时间变异性会加剧考生的时间焦虑,因此减少超长的考生数量和考生之间的应试时间差异至关重要。为了满足这些实际需求,本文提出了阶段适应性的新思想,将项目选择过程定制为每个步骤的决策需求,并对现有的响应时间选择方法产生新的见解。结果表明,通过新方法,考生可以实现平衡的项目使用以及短而稳定的考试时间。
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来源期刊
CiteScore
5.00
自引率
3.80%
发文量
34
审稿时长
>12 weeks
期刊介绍: The British Journal of Mathematical and Statistical Psychology publishes articles relating to areas of psychology which have a greater mathematical or statistical aspect of their argument than is usually acceptable to other journals including: • mathematical psychology • statistics • psychometrics • decision making • psychophysics • classification • relevant areas of mathematics, computing and computer software These include articles that address substantitive psychological issues or that develop and extend techniques useful to psychologists. New models for psychological processes, new approaches to existing data, critiques of existing models and improved algorithms for estimating the parameters of a model are examples of articles which may be favoured.
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