More than three decades after their introduction, diagnostic classification models (DCM) do
not seem to have been implemented in educational systems for the purposes they were …

Diagnostic classification tests are designed to assess examinees' discrete mastery status on
a set of skills or attributes. Such tests have gained increasing attention in educational and …

The rapid development of the technologies for online learning provides students with
extensive resources for self-learning and brings new opportunities for data-driven research …

Complexity in item response theory (IRT) has traditionally been quantified by simply
counting the number of freely estimated parameters in the model. However, complexity is …

Intelligent education systems have enabled personalized learning (PL). In PL, students are
presented with educational contents that are consistent with their personal knowledge states …

This article focuses on a family of restricted latent structure models with wide applications in
psychological and educational assessment, where the model parameters are restricted via a …

Cognitive diagnosis models are partially ordered latent class models and are used to
classify students into skill mastery profiles. The deterministic inputs, noisy “and” gate model …

An adaptive learning system aims at providing instruction tailored to the current status of a
learner, differing from the traditional classroom experience. The latest advances in …

Statistical latent class models are widely used in social and psychological researches, yet it
is often difficult to establish the identifiability of the model parameters. In this paper, we …

Diagnostic classification models (DCMs) are important statistical tools in cognitive diagnosis.
In this paper, we consider the issue of their identifiability. In particular, we focus on one basic …