Using data from multiple informants has long been considered best practice in education. However, multiple informants often disagree on similar constructs, complicating decision-making. Polynomial regression and response-surface analysis (PRA) is often used to test the congruence effect between multiple informants on an outcome. However, PRA…

Although Diagnostic Classification Models (DCMs) were introduced to education system decades ago, it seems that these models were not employed for the original aims upon which they had been designed. Using DCMs has been mostly common in analyzing large-scale non-diagnostic tests and these models have been rarely used in developing Cognitive…

Most of the existing classification accuracy indices of attribute patterns lose effectiveness when the response data is absent in diagnostic testing. To handle this issue, this article proposes new indices to predict the correct classification rate of a diagnostic test before administering the test under the deterministic noise input…

We investigated the classification accuracy of learning disability (LD) identification methods premised on the identification of an intraindividual pattern of processing strengths and weaknesses (PSW) method using multiple indicators for all latent constructs. Known LD status was derived from latent scores; values at the observed level identified…

This contribution briefly sketches the evolvement of numeracy or mathematical literacy as models for mathematics curricula, which will be described as driven by a weakening of the insulation between discourses, that is, as a process of "declassification". The question then arises as to whether and how coherence of new forms of initially…

Diagnostic classification models (aka cognitive or skills diagnosis models) have shown great promise for evaluating mastery on a multidimensional profile of skills as assessed through examinee responses, but continued development and application of these models has been hindered by a lack of readily available software. In this article we…

Interest in developing computerized adaptive testing (CAT) under cognitive diagnosis models (CDMs) has increased recently. CAT algorithms that use a fixed-length termination rule frequently lead to different degrees of measurement precision for different examinees. Fixed precision, in which the examinees receive the same degree of measurement…

Over the past 20 years, there has been much research on how people learn from case comparisons. This work has implemented comparison activities in a variety of different ways across a wide range of laboratory and classroom contexts. In an effort to assess the overall effectiveness of case comparisons across this diversity of implementation and…

Retrieving information from memory produces more learning than does being presented with the same information, and the benefits of such retrieval appear to grow as the delay before a final recall test grows longer. Recall tests, however, measure the number of items that are above a recall threshold, not memory strength per se. According to the…

Though calibration of an achievement test within psychological and educational context is very often carried out by the Rasch model, data sampling is hardly designed according to statistical foundations. However, Kubinger, Rasch, and Yanagida (2009) recently suggested an approach for the determination of sample size according to a given Type I and…

Implications of the International Classification of Functioning, Disability and Health (ICF) on the development and use of tests in school settings are enumerated. We predict increased demand for behavioural assessments that consider a person's activities, participation and person-environment interactions, including measures that: (a) address…

This article investigates how measurement models and statistical procedures can be applied to estimate the accuracy of proficiency classification in language testing. The paper starts with a concise introduction of four measurement models: the classical test theory (CTT) model, the dichotomous item response theory (IRT) model, the testlet response…

In this commentary, the author points out few issues, one being that there are models mislabeled as diagnostic, which deal with linear decompositions of item difficulties rather than estimating multidimensional skill variables. The author discusses the issue that there are many new names for essentially well-known models for multiple simultaneous…

As Rupp and Templin (2008) stated directly, diagnostic classification methods "are confirmatory in nature." Methods, though, are neither inherently confirmatory nor exploratory. Diagnostic classification modeling, with its analytical and computational obstacles eventually yielding as a comprehensive and potent discipline emerges, will…

The paper by Rupp and Templin (2008) is an excellent work on the characteristics and features of cognitive diagnostic models (CDM). In this article, the authors comment on some substantial and methodological aspects of this focus paper. They organize their comments by going through issues associated with the terms "cognitive,"…