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Product details:
- ISBN-10 : 3030055841
- ISBN-13 : 9783030055844
- Author: Matthias Von Davier
This handbook provides an overview of major developments around diagnostic classification models (DCMs) with regard to modeling, estimation, model checking, scoring, and applications. It brings together not only the current state of the art, but also the theoretical background and models developed for diagnostic classification. The handbook also offers applications and special topics and practical guidelines how to plan and conduct research studies with the help of DCMs. Commonly used models in educational measurement and psychometrics typically assume a single latent trait or at best a small number of latent variables that are aimed at describing individual differences in observed behavior. While this allows simple rankings of test takers along one or a few dimensions, it does not provide a detailed picture of strengths and weaknesses when assessing complex cognitive skills. DCMs, on the other hand, allow the evaluation of test taker performance relative to a potentially large number of skill domains
Table of contents:
1. Introduction: From Latent Classes to Cognitive Diagnostic Models
Part I. Approaches to Cognitive Diagnosis
2. Nonparametric Item Response Theory and Mokken Scale Analysis, with Relations to Latent Class Models and Cognitive Diagnostic Models
3. The Reparameterized Unified Model System: A Diagnostic Assessment Modeling Approach
4. Bayesian Networks
5. Nonparametric Methods in Cognitively Diagnostic Assessment
6. The General Diagnostic Model
7. The G-DINA Model Framework
8. Loglinear Cognitive Diagnostic Model (LCDM)
9. Diagnostic Modeling of Skill Hierarchies and Cognitive Processes with MLTM-D
10. Explanatory Cognitive Diagnostic Models
11. Insights from Reparameterized DINA and Beyond
Part II. Special Topics
12. Q-Matrix Learning via Latent Variable Selection and Identifiability
13. Global- and Item-Level Model Fit Indices
14. Exploratory Data Analysis for Cognitive Diagnosis: Stochastic Co-blockmodel and Spectral Co-clustering
15. Recent Developments in Cognitive Diagnostic Computerized Adaptive Testing (CD-CAT): A Comprehensive Review
16. Identifiability and Cognitive Diagnosis Models
17. Measures of Agreement: Reliability, Classification Accuracy, and Classification Consistency
18. Differential Item Functioning in Diagnostic Classification Models
19. Bifactor MIRT as an Appealing and Related Alternative to CDMs in the Presence of Skill Attribute Continuity
Part III. Applications
20. Utilizing Process Data for Cognitive Diagnosis
21. Application of Cognitive Diagnostic Models to Learning and Assessment Systems
22. CDMs in Vocational Education: Assessment and Usage of Diagnostic Problem-Solving Strategies in Car Mechatronics
23. Applying the General Diagnostic Model to Proficiency Data from a National Skills Survey
24. Reduced Reparameterized Unified Model Applied to Learning Spatial Rotation Skills
25. How to Conduct a Study with Diagnostic Models
Part IV. Software, Data, and Tools
26. The R Package CDM for Diagnostic Modeling
27. Diagnostic Classification Modeling with flexMIRT
28. Using Mplus to Estimate the Log-Linear Cognitive Diagnosis Model
29. Cognitive Diagnosis Modeling Using the GDINA R Package
30. GDM Software mdltm Including Parallel EM Algorithm
31. Estimating CDMs Using MCMC
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