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.

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Publication Details

Journal
Journal of Mathematical Psychology
Published
2025-05-01
DOI
https://doi.org/10.1016/j.jmp.2025.102926
Primary Topic
Psychometric Methodologies and Testing
Type
article
Field-Weighted Citation Impact
0.00

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article

Toward a unified perspective on assessment models, part II: Dichotomous latent variables

Sangbeak Ye, Jürgen Heller, Stefano Noventa, Augustin Kelava
Journal of Mathematical Psychology
Psychometric Methodologies and Testing
article

Toward a unified perspective on assessment models, part II: Dichotomous latent variables

Sangbeak Ye, Jürgen Heller, Stefano Noventa, Augustin Kelava
article en

Abstract

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.

Journal of Mathematical PsychologyVol. 125
Deutsche Forschungsgemeinschaft
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Psychometric Methodologies and Testing
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Toward a unified perspective on assessment models, part II: Dichotomous latent variables — Sangbeak Ye, Jürgen Heller, et al. · Journal of Mathematical Psychology (2025) | TGRS Research Map | TGRS