Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 0 |
| Since 2006 (last 20 years) | 2 |
Descriptor
| Computation | 2 |
| Computer Assisted Testing | 2 |
| Models | 2 |
| Test Items | 2 |
| Accuracy | 1 |
| Adaptive Testing | 1 |
| Bayesian Statistics | 1 |
| Goodness of Fit | 1 |
| Markov Processes | 1 |
| Monte Carlo Methods | 1 |
| Reaction Time | 1 |
| More ▼ | |
Author
| Chang, Hua-Hua | 2 |
| Douglas, Jeffrey A. | 1 |
| Fan, Zhewen | 1 |
| Wang, Chun | 1 |
| Ying, Zhiliang | 1 |
Publication Type
| Journal Articles | 2 |
| Reports - Evaluative | 1 |
| Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkWang, Chun; Fan, Zhewen; Chang, Hua-Hua; Douglas, Jeffrey A. – Journal of Educational and Behavioral Statistics, 2013
The item response times (RTs) collected from computerized testing represent an underutilized type of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. Current models for RTs mainly focus on parametric models, which have the…
Descriptors: Reaction Time, Computer Assisted Testing, Test Items, Accuracy
Chang, Hua-Hua; Ying, Zhiliang – Psychometrika, 2008
It has been widely reported that in computerized adaptive testing some examinees may get much lower scores than they would normally if an alternative paper-and-pencil version were given. The main purpose of this investigation is to quantitatively reveal the cause for the underestimation phenomenon. The logistic models, including the 1PL, 2PL, and…
Descriptors: Adaptive Testing, Computer Assisted Testing, Computation, Test Items
