Teamwork Cognitive Diagnostic Modeling.

IF 3.1 2区 心理学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Peida Zhan, Zhimou Wang, Gaohong Chu, Haixin Qiao
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引用次数: 0

Abstract

Teamwork relies on collaboration to achieve goals that exceed individual capabilities, with team cognition playing a key role by integrating individual expertise and shared understanding. Identifying the causes of inefficiencies or poor team performance is critical for implementing targeted interventions and fostering the development of team cognition. This study proposes a teamwork cognitive diagnostic modeling framework comprising 12 specific models-collectively referred to as Team-CDMs-which are designed to capture the interdependence among team members through emergent team cognitions by jointly modeling individual cognitive attributes and a team-level construct, termed teamwork quality, which reflects the social dimension of collaboration. The models can be used to identify strengths and weaknesses in team cognition and determine whether poor performance arises from cognitive deficiencies or social issues. Two simulation studies were conducted to assess the psychometric properties of the models under diverse conditions, followed by a teamwork reasoning task to demonstrate their application. The results showed that Team-CDMs achieve robust parameter estimation, effectively diagnose individual attributes, and assess teamwork quality while pinpointing the causes of poor performance. These findings underscore the utility of Team-CDMs in understanding, diagnosing, and improving team cognition, offering a foundation for future research and practical applications in teamwork-based assessments.

团队认知诊断模型。
团队合作依靠协作来实现超越个人能力的目标,团队认知通过整合个人专业知识和共享理解发挥关键作用。确定效率低下或团队绩效差的原因对于实施有针对性的干预和促进团队认知的发展至关重要。本研究提出了一个团队认知诊断模型框架,该模型包括12个具体模型(统称为team- cdms),旨在通过共同建模个体认知属性和团队层面的团队素质(反映协作的社会维度),通过突发团队认知捕捉团队成员之间的相互依存关系。这些模型可以用来识别团队认知的优势和劣势,并确定绩效不佳是由认知缺陷还是社会问题引起的。通过两个模拟研究来评估模型在不同条件下的心理测量特性,然后通过团队推理任务来演示模型的应用。结果表明,团队- cdms实现了稳健的参数估计,有效地诊断个体属性,并在确定绩效不佳原因的同时评估团队质量。这些发现强调了team - cdm在理解、诊断和提高团队认知方面的效用,为未来的研究和基于团队的评估的实际应用奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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