Although the generalized deterministic inputs, noisy "and" gate model (G-DINA; de la Torre, 2011) is a general cognitive diagnosis model (CDM), it does not account for the heterogeneity that is rooted from the existing latent groups in the population of examinees. To address this, this study proposes the mixture G-DINA model, a CDM that…

In this article, we propose a variational Bayes (VB) inference method for the deterministic input noisy AND gate model of cognitive diagnostic assessment. The proposed method, which applies the iterative algorithm for optimization, is derived based on the optimal variational posteriors of the model parameters. The proposed VB inference enables…

The log-linear cognitive diagnosis model (LCDM) is a modern technique that dichotomously classifies individuals (e.g., possession and non-possession) on attributes of a multidimensional construct, which is particularly suited to diagnostic and formative assessments where a classification decision is desired (e.g., to assign intervention or not).…

Although much research has been conducted on the psychometric properties of cognitive diagnostic models, they are only recently being used in operational settings to provide results to examinees and other stakeholders. Using this newer class of models in practice comes with a fresh challenge for diagnostic assessment developers: effectively…

In this article, we systematically introduce the just another Gibbs sampler (JAGS) software program to fit common Bayesian cognitive diagnosis models (CDMs) including the deterministic inputs, noisy "and" gate model; the deterministic inputs, noisy "or" gate model; the linear logistic model; the reduced reparameterized unified…

Cognitive Diagnostic Assessment (CDA) is a type of educational assessment that is designed to measure specific knowledge structures and processing skills in students so as to provide information about their cognitive strengths and weaknesses (Leighton & Gierl, 2007). CDA has been instrumental in turning the attention of practitioners to more…

Cognitive diagnostic models (CDM) have been around for more than a decade but their application is far from widespread for mainly two reasons: (1) CDMs are novel, as compared to traditional IRT models. Consequently, many researchers lack familiarity with them and their properties, and (2) Software programs doing CDMs have been expensive and not…

Scientific literacy is now seen as an essential component of informed citizenship and a key curriculum goal in many parts of the world. The relevant literature is vast and replete with a variety of definitions, descriptions, prescriptions, slogans and theoretical perspectives. It addresses not only formal education but also fields as diverse as…

In episodic memory tasks, associations are formed between items presented close together in time. The temporal context model (TCM) hypothesizes that this contiguity effect is a consequence of shared temporal context rather than temporal proximity per se. Using double-function lists of paired associates (e.g., A-B, B-C) presented in a random order,…

Modern factor analysis is the outgrowth of Spearman's original "2-factor" model of intelligence, according to which a mental test score is regarded as the sum of a general factor and a specific factor. As early as 1914, Godfrey Thomson realized that the data did not require this interpretation and he demonstrated this by proposing what became…

The purpose of this paper is to describe the logic and identify key assumptions associated with making cognitive inferences using two attribute-based psychometric methods. The first method is Kikumi Tatsuoka's rule-space model. This model provides a strong point of reference for studying the nature of diagnostic inferences because it is important…

The "universal to unique" framework of educational psychology is intended to provide a balance between developmental psychology's holistic approach to learning theory and cognitive psychology's emphasis on individual differences. (Author/JCD)

This paper describes a comprehensive model of alignment that provides a foundation for meaningful reporting of students' academic progress over time. The model includes both horizontal and vertical alignment as integral parts of the development of content standards, test blueprints, items, item pools, instruments, performance level descriptors,…

This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…

Cognitive diagnosis models are constrained (multiple classification) latent class models that characterize the relationship of questionnaire responses to a set of dichotomous latent variables. Having emanated from educational measurement, several aspects of such models seem well suited to use in psychological assessment and diagnosis. This article…