Sample size requirements for applying diagnostic classification models
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 …
size, test length, number of attributes and base rate of mastery on item parameter recovery …
Nonparametric classification method for multiple-choice items in cognitive diagnosis
The multiple-choice (MC) item format has been widely used in educational assessments
across diverse content domains. MC items purportedly allow for collecting richer diagnostic …
across diverse content domains. MC items purportedly allow for collecting richer diagnostic …
Semisupervised learning method to adjust biased item difficulty estimates caused by nonignorable missingness in a virtual learning environment
K Xue, AC Huggins-Manley… - Educational and …, 2022 - journals.sagepub.com
In data collected from virtual learning environments (VLEs), item response theory (IRT)
models can be used to guide the ongoing measurement of student ability. However, such …
models can be used to guide the ongoing measurement of student ability. However, such …
A semi-supervised learning-based diagnostic classification method using artificial neural networks
K Xue, LP Bradshaw - Frontiers in Psychology, 2021 - frontiersin.org
The purpose of cognitive diagnostic modeling (CDM) is to classify students' latent attribute
profiles using their responses to the diagnostic assessment. In recent years, each diagnostic …
profiles using their responses to the diagnostic assessment. In recent years, each diagnostic …
Applying support vector machines to a diagnostic classification model for polytomous attributes in small‐sample contexts
X Li, S Dong, S Guo, C Zheng - British Journal of Mathematical …, 2024 - Wiley Online Library
Over several years, the evaluation of polytomous attributes in small‐sample settings has
posed a challenge to the application of cognitive diagnosis models. To enhance …
posed a challenge to the application of cognitive diagnosis models. To enhance …
A Comparison of the Classification Performances of the DINO Model, Artificial Neural Networks and Non-Parametric Cognitive Diagnosis
E Yavuz, HY Atar - Journal of Measurement and Evaluation in …, 2023 - dergipark.org.tr
The purpose of this study was to compare the attribute (ACR) and pattern-level (PCR)
classification rates of the Deterministic-Input, Noisy-Or Gate (DINO) model, Artificial Neural …
classification rates of the Deterministic-Input, Noisy-Or Gate (DINO) model, Artificial Neural …
EW-KNN: evaluating information technology courses in high school with a non-parametric cognitive diagnosis method
W Zhang, L Meng, B Liang - Interactive Learning Environments, 2023 - Taylor & Francis
With the continuous development of education, personalized learning has attracted great
attention. How to evaluate students' learning effects has become increasingly important. In …
attention. How to evaluate students' learning effects has become increasingly important. In …
Evaluation of the goodness-of-fit index Mord in polytomous DCMs with hierarchical attribute structures
H Yuan - 2022 - search.proquest.com
The application of diagnostic classification models (DCMs) in the field of educational
measurement is getting more attention in recent years. To make a valid inference from the …
measurement is getting more attention in recent years. To make a valid inference from the …