Diagnostic classification models: Recent developments, practical issues, and prospects
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 …
not seem to have been implemented in educational systems for the purposes they were …
Statistical applications to cognitive diagnostic testing
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 …
a set of skills or attributes. Such tests have gained increasing attention in educational and …
Learning or forgetting? A dynamic approach for tracking the knowledge proficiency of students
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 …
extensive resources for self-learning and brings new opportunities for data-driven research …
On the complexity of item response theory models
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 …
counting the number of freely estimated parameters in the model. However, complexity is …
Knowledge modeling via contextualized representations for LSTM-based personalized exercise recommendation
Intelligent education systems have enabled personalized learning (PL). In PL, students are
presented with educational contents that are consistent with their personal knowledge states …
presented with educational contents that are consistent with their personal knowledge states …
Identifying latent structures in restricted latent class models
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 …
psychological and educational assessment, where the model parameters are restricted via a …
Bayesian estimation of the DINA Q matrix
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 …
classify students into skill mastery profiles. The deterministic inputs, noisy “and” gate model …
Recommendation system for adaptive learning
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 …
learner, differing from the traditional classroom experience. The latest advances in …
Identifiability of restricted latent class models with binary responses
G Xu - 2017 - projecteuclid.org
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 …
is often difficult to establish the identifiability of the model parameters. In this paper, we …
Identifiability of diagnostic classification models
G Xu, S Zhang - Psychometrika, 2016 - Springer
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 …
In this paper, we consider the issue of their identifiability. In particular, we focus on one basic …