A New Measurement of Internet Addiction Using Diagnostic Classification Models [PDF]
Frontiers in Psychology, 2017 To obtain accurate, valid, and rich information from the questionnaires for internet addiction, a diagnostic classification test for internet addiction (the DCT-IA) was developed using diagnostic classification models (DCMs), a cutting-edge psychometric ...
Dongbo Tu +3 more
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Assessing Language Skills Using Diagnostic Classification Models: An Example Using a Language Instrument [PDF]
International Journal of Psychological Research, 2022 The primary purpose of the present study was to inform and illustrate, using examples, the use of Diagnostic Classification Models (DCMs) for the assessment of skills and competencies in cognition and academic achievement.
Georgios D. Sideridis +2 more
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Sample Size Requirements for Applying Diagnostic Classification Models [PDF]
Frontiers in Psychology, 2021 Results of a comprehensive simulation study are reported investigating the effects of sample size, test length, number of attributes and base rate of mastery on item parameter recovery and classification accuracy of four DCMs (i.e., C-RUM, DINA, DINO ...
Sedat Sen, Allan S. Cohen
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Diagnostic Classification Models for Ordinal Item Responses [PDF]
Frontiers in Psychology, 2018 The purpose of this study is to develop and evaluate two diagnostic classification models (DCMs) for scoring ordinal item data. We first applied the proposed models to an operational dataset and compared their performance to an epitome of current ...
Ren Liu, Zhehan Jiang
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Applying the M2 Statistic to Evaluate the Fit of Diagnostic Classification Models in the Presence of Attribute Hierarchies [PDF]
Frontiers in Psychology, 2018 The performance of the limited-information statistic M2 for diagnostic classification models (DCMs) is under-investigated in the current literature. Specifically, the investigations of M2 for specific DCMs rather than general modeling frameworks are ...
Fu Chen, Yanlou Liu, Tao Xin, Ying Cui
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Language Testing in Asia, 2021 The current study compared the model fit indices, skill mastery probabilities, and classification accuracy of six Diagnostic Classification Models (DCMs): a general model (G-DINA) against five specific models (LLM, RRUM, ACDM, DINA, and DINO).
Mahdieh Shafipoor +2 more
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Q-Matrix Designs of Longitudinal Diagnostic Classification Models With Hierarchical Attributes for Formative Assessment [PDF]
Frontiers in Psychology, 2020 Longitudinal diagnostic classification models (DCMs) with hierarchical attributes can characterize learning trajectories in terms of the transition between attribute profiles for formative assessment.
Wei Tian +3 more
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Automated detection of freeze-thaw signatures in archaeological sediments using deep learning [version 2; peer review: 1 approved, 2 approved with reservations] [PDF]
Open Research EuropeBackground Freeze-thaw processes leave diagnostic traces in archaeological soils and sediments that are central to reconstructing past climates and understanding hominin adaptations to glacial environments.
Li Li, Sofia Kouki, Vera Aldeias
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Frontiers in EducationDiagnostic classification models (DCM) have been a recent topic of conversation in the development of educational materials. Specifically, there has been significant criticism of their validity and use within the educational system.
Matias Urrutia-Jorde
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Navigating the complexity of WHO CNS5: the evolutionary trajectory of glioma classification and the emergence of large language models [PDF]
Frontiers in OncologyThe 2021 World Health Organization (WHO) Classification of Tumors of the Central Nervous System (fifth edition, WHO CNS5) marks a profound paradigm shift from traditional morphologic assessment to a biologically and molecularly integrated diagnostic ...
Minghao Lian +5 more
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