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Deep cognitive diagnosis model for predicting students’ performance
Future Generation Computer Systems, 2022Abstract Cognitive model is playing very important role in predicting students’ performance and recommending learning resources. Thus, it has received a great deal of attention from researchers. However, most of the existing work design models from the aspect of students, ignoring the internal relation between problems and skills.
Lina Gao +4 more
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Evaluation of Model Fit in Cognitive Diagnosis Models
International Journal of Testing, 2016Cognitive diagnosis models (CDMs) estimate student ability profiles using latent attributes. Model fit to the data needs to be ascertained in order to determine whether inferences from CDMs are valid. This study investigated the usefulness of some popular model fit statistics to detect CDM fit including relative fit indices (AIC, BIC, and CAIC), and ...
Jinxiang Hu +3 more
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A Cognitive Diagnosis Model for Cognitively Based Multiple-Choice Options
Applied Psychological Measurement, 2009Cognitive or skills diagnosis models are discrete latent variable models developed specifically for the purpose of identifying the presence or absence of multiple fine-grained skills. However, applications of these models typically involve dichotomous or dichotomized data, including data from multiple-choice (MC) assessments that are scored as right or
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A Cognitive Diagnosis Model for Continuous Response
Journal of Educational and Behavioral Statistics, 2017Nondichotomous response models have been of greater interest in recent years due to the increasing use of different scoring methods and various performance measures. As an important alternative to dichotomous scoring, the use of continuous response formats has been found in the literature.
Liu, Y, Minchen, N, de la Torre, J
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Computational Cognitive Modeling for the Diagnosis of Specific Language Impairment
2013Specific Language Impairment (SLI), as many other cognitive deficits, is difficult to diagnose given its heterogeneous profile and its overlap with other impairments. Existing techniques are based on different criteria using behavioral variables on different tasks.
Jesus Oliva +3 more
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Cognitive diagnosis modelling incorporating item response times
British Journal of Mathematical and Statistical Psychology, 2017To provide more refined diagnostic feedback with collateral information in item response times ( RT s), this study proposed joint modelling of attributes and response speed using item responses and RT s simultaneously for cognitive diagnosis.
Peida Zhan, Hong Jiao, Dandan Liao
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A “Learning from Models” Cognitive Fault Diagnosis System
2012We present an unsupervised cognitive fault diagnosis framework for nonlinear dynamic systems working in the space of approximating models. The diagnosis system detects and classifies faults by relying on a fault dictionary that is empty at the beginning of the system's life and is automatically populated as faults occur.
ALIPPI, CESARE +2 more
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Diagnosis in SEMS Based on Cognitive Models
2018Problem statement: SEMS is a complex dynamic object in the operational phase of which it is likely that abnormal situations may occur in which the state of the equipment goes beyond the normal functioning, which can subsequently lead to an accident. Despite the importance of the need and importance of effectively solving the problems of diagnostics of ...
Vladimir V. Korobkin +1 more
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Identifiability and Cognitive Diagnosis Models
2019Cognitive Diagnosis Models (CDMs) are popular statistical tools in cognitive diagnosis assessment. CDMs can be viewed as restricted latent class models with constraints introduced by the Q-matrix and assumptions of how skill variables that are assigned to items via the Q-Matrix interact in the item function. As many other latent variable models do, the
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Abstract: A Hierarchical Item Response Model for Cognitive Diagnosis
Multivariate Behavioral Research, 2013Cognitive diagnosis models (see, e.g., Rupp, Templin, & Henson, 2010) have received increasing attention within educational and psychological measurement.
Mark, Hansen, Li, Cai
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