This study proposes a Bayesian method for diagnostic classification models (DCMs) for a partially known Q-matrix setting between exploratory and confirmatory DCMs. This Q-matrix setting is practical and useful because test experts have pre-knowledge of the Q-matrix but cannot readily specify it completely. The proposed method employs priors for…

Diagnostic classification models (DCMs) are psychometric models that can be used to estimate the presence or absence of psychological traits, or proficiency on fine-grained skills. Critical to the use of any psychometric model in practice, including DCMs, is an evaluation of model fit. Traditionally, DCMs have been estimated with maximum…

To model behavioral and neural correlates of language comprehension in naturalistic environments, researchers have turned to broad-coverage tools from natural-language processing and machine learning. Where syntactic structure is explicitly modeled, prior work has relied predominantly on context-free grammars (CFGs), yet such formalisms are not…

In learning diagnostic assessments, the attribute hierarchy specifies a sequential network of interrelated attribute mastery processes, which makes a test blueprint consistent with the cognitive theory. One of the most important functions of attribute hierarchy is to guide or limit the developmental direction of students and then form a…

The forced-choice (FC) item formats used for noncognitive tests typically develop a set of response options that measure different traits and instruct respondents to make judgments among these options in terms of their preference to control the response biases that are commonly observed in normative tests. Diagnostic classification models (DCMs)…

Purpose: ParAlg (Paraphasia Algorithms) is a software that automatically categorizes a person with aphasia's naming error (paraphasia) in relation to its intended target on a picture-naming test. These classifications (based on lexicality as well as semantic, phonological, and morphological similarity to the target) are important for…

The drift diffusion model (DDM) is a widely applied computational model of decision making that allows differentiation between latent cognitive and residual processes. One main assumption of the DDM that has undergone little empirical testing is the level of independence between cognitive and motor responses. If true, widespread incorporation of…

The study of mind-wandering is popular since it is linked to the emotional problems and working/learning performance. In terms of education, it impacts comprehension during learning which affects academic success. Therefore, we sought to develop a machine learning model for an embedded portable device that can categorize mind-wandering state to…

This article critically reviews how diagnostic models have been conceptualized and how they compare to other approaches used in educational measurement. In particular, certain assumptions that have been taken for granted and used as defining characteristics of diagnostic models are reviewed and it is questioned whether these assumptions are the…

Behavioral research has shown that 12- but not 9-month-olds imitate an unusual and inefficient action (turning on a lamp with one's forehead) more when the model's hands are free. Rational-imitation accounts suggest that infants evaluate actions based on the rationality principle, that is, they expect people to choose efficient means to achieve a…

The present study examined the performance of the bi-factor multidimensional item response theory (MIRT) model and higher-order (HO) cognitive diagnostic models (CDM) in providing diagnostic information and general ability estimation simultaneously in a listening test. The data used were 1,611 examinees' item-level responses to an in-house EFL…

Introduction: So far some methods to help diagnosis of ADHD grounded in EEG decomposition by the FFT method and the discovery of the relationship between different frequency bands, the most clarifying the TBR rate in the prefrontal regions, have been proposed. This procedure requires a complex gadgetry so we evaluate the advantages of a simple…

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with social communication deficits as one of the core symptoms. Recently, a five-level model for the social communication has been proposed in which white matter tracts corresponding to each level of the model are identified. Given that the model for social communication…

Cognitive diagnostic models (CDMs) have great promise for providing diagnostic information to aid learning and instruction, and a large number of CDMs have been proposed. However, the assumptions and performances of different CDMs and their applications in regard to reading comprehension tests are not fully understood. In the present study, we…

In this study, two alternative theoretical models were compared, in order to analyze which of them best explains primary school children's text comprehension skills. The first one was based on the distinction between two types of answers requested by the comprehension test: local or global. The second model involved texts' input modality: written…