Computerized Adaptive Testing Using the Partial Credit Model
Effects Of Item Pool Characteristics and Different Stopping Rules
Bibliographic Data
| ID | 20286452 |
|---|---|
| Authors | Barbara G Dodd (The University of Texas at Austin), William R Koch (0000-0002-3982-482X, The University of Texas at Austin), Ralph J De Ayala (University of Maryland, College Park) |
| Year | 1993 |
| Volume | 53 |
| Issue | 1 |
| Pages | 61-77 |
| Publication date | 1993-03-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Educational and Psychological Measurement (JOURNAL) |
| Journal identifiers | ISSN: 0013-1644 • E-ISSN: 1552-3888 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/0013164493053001005 |
| OpenAlex | W2172088011 |
| Language | EN |
| Citations received | 4 |
| References cited | 9 |
Simulated datasets were used to research the effects of the systematic variation of three major variables on the performance of computerized adaptive testing (CAT) procedures for the partial credit model. The three variables studied were the stopping rule for terminating the CATs, item pool size, and the distribution of the difficulty of the items in the pool. Results indicated that the standard error stopping rule performed better across the variety of CAT conditions than the minimum information stopping rule. In addition it was found that item pools that consisted of as few as 30 items were adequate for CAT provided that the item pool was of medium difficulty. The implications of these findings for implementing CAT systems based on the partial credit model are discussed
Computerized adaptive testing · Econometrics · Psychometrics · Statistics · Variety (cybernetics) · Advanced Statistical Modeling Techniques · Computer Science · Mathematics · Psychometric Methodologies and Testing
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A Comparison of Maximum Likelihood Estimation and Expected a Posteriori Estimation in CAT Using the Partial Credit Model
A New Stopping Rule for Computerized Adaptive Testing
The Effect of Population Distribution and Method of Theta Estimation on Computerized Adaptive Testing (CAT) Using the Rating Scale Model
| Citations per year | 0.14 |
|---|---|
| Citation span | 1997 - 2022 (26) |
| Highly cited | No |