Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 1 |
Descriptor
| Accuracy | 1 |
| Achievement Tests | 1 |
| Algorithms | 1 |
| Bayesian Statistics | 1 |
| Computation | 1 |
| Data Analysis | 1 |
| Data Collection | 1 |
| Data Processing | 1 |
| Educational Assessment | 1 |
| Educational Testing | 1 |
| Evaluation Methods | 1 |
| More ▼ | |
Source
| Grantee Submission | 1 |
Publication Type
| Reports - Research | 1 |
Education Level
| Secondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
| Program for International… | 1 |
What Works Clearinghouse Rating
Peer reviewed
Direct linkSainan Xu; Jing Lu; Jiwei Zhang; Chun Wang; Gongjun Xu – Grantee Submission, 2024
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…
Descriptors: Educational Assessment, Bayesian Statistics, Statistical Inference, Item Response Theory
