Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 3 |
Since 2006 (last 20 years) | 3 |
Descriptor
Author
Arenson, Ethan A. | 1 |
Chen, Changsheng | 1 |
Delafontaine, Jolien | 1 |
Dirlik, Ezgi Mor | 1 |
Karabatsos, George | 1 |
Park, Jung Yeon | 1 |
Van den Noortgate, Wim | 1 |
Publication Type
Journal Articles | 2 |
Reports - Research | 2 |
Reports - Descriptive | 1 |
Education Level
Elementary Secondary Education | 3 |
Elementary Education | 1 |
Grade 8 | 1 |
Junior High Schools | 1 |
Middle Schools | 1 |
Secondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
Trends in International… | 3 |
What Works Clearinghouse Rating
Delafontaine, Jolien; Chen, Changsheng; Park, Jung Yeon; Van den Noortgate, Wim – Large-scale Assessments in Education, 2022
In cognitive diagnosis assessment (CDA), the impact of misspecified item-attribute relations (or "Q-matrix") designed by subject-matter experts has been a great challenge to real-world applications. This study examined parameter estimation of the CDA with the expert-designed Q-matrix and two refined Q-matrices for international…
Descriptors: Q Methodology, Matrices, Cognitive Measurement, Diagnostic Tests
Dirlik, Ezgi Mor – International Journal of Progressive Education, 2019
Item response theory (IRT) has so many advantages than its precedent Classical Test Theory (CTT) such as non-changing item parameters, ability parameter estimations free from the items. However, in order to get these advantages, some assumptions should be met and they are; unidimensionality, normality and local independence. However, it is not…
Descriptors: Comparative Analysis, Nonparametric Statistics, Item Response Theory, Models
Arenson, Ethan A.; Karabatsos, George – Grantee Submission, 2017
Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. We propose a simple and more flexible Bayesian nonparametric IRT model…
Descriptors: Bayesian Statistics, Item Response Theory, Nonparametric Statistics, Models