Stefano Noventa , Jürgen Heller , Sangbeak Ye , Augustin Kelava
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Toward a unified perspective on assessment models, part II: Dichotomous latent variables
In the past years, several theories for assessment have been developed within the fields of Psychometrics and Mathematical Psychology. The most notable are Item Response Theory (IRT), Cognitive Diagnostic Assessment (CDA), and Knowledge Structure Theory (KST). In spite of their common goals, these theories have been developed largely independently, focusing on slightly different aspects. In Part I of this three-part work, a general framework was introduced with the aim of achieving a unified perspective. The framework consists of two primitives (structure and process) and two operations (factorization and reparametrization) that allow to derive the models of these theories and systematize them within a general taxonomy. In this second contribution, the framework introduced in Part I is used to derive both KST and CDA models based on dichotomous latent variables, thus achieving a two-fold result: On the one hand, it settles the relation between the frameworks; On the other hand, it provides a simultaneous generalization of both frameworks, thus providing the foundations for the analysis of more general models and situations.
期刊介绍:
The Journal of Mathematical Psychology includes articles, monographs and reviews, notes and commentaries, and book reviews in all areas of mathematical psychology. Empirical and theoretical contributions are equally welcome.
Areas of special interest include, but are not limited to, fundamental measurement and psychological process models, such as those based upon neural network or information processing concepts. A partial listing of substantive areas covered include sensation and perception, psychophysics, learning and memory, problem solving, judgment and decision-making, and motivation.
The Journal of Mathematical Psychology is affiliated with the Society for Mathematical Psychology.
Research Areas include:
• Models for sensation and perception, learning, memory and thinking
• Fundamental measurement and scaling
• Decision making
• Neural modeling and networks
• Psychophysics and signal detection
• Neuropsychological theories
• Psycholinguistics
• Motivational dynamics
• Animal behavior
• Psychometric theory