Computerized Adaptive Testing Using a Class of High-Order Item Response Theory Models
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| Title: | Computerized Adaptive Testing Using a Class of High-Order Item Response Theory Models |
|---|---|
| Language: | English |
| Authors: | Huang, Hung-Yu, Chen, Po-Hsi, Wang, Wen-Chung |
| Source: | Applied Psychological Measurement. Nov 2012 36(8):689-706. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com |
| Peer Reviewed: | Y |
| Physical Description: | |
| Page Count: | 18 |
| Publication Date: | 2012 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Computer Assisted Testing, Adaptive Testing, Item Response Theory, Simulation, Test Items, Item Analysis, Selection, Item Banks |
| DOI: | 10.1177/0146621612459552 |
| ISSN: | 0146-6216 |
| Abstract: | In the human sciences, a common assumption is that latent traits have a hierarchical structure. Higher order item response theory models have been developed to account for this hierarchy. In this study, computerized adaptive testing (CAT) algorithms based on these kinds of models were implemented, and their performance under a variety of situations was examined using simulations. The results showed that the CAT algorithms were very effective. The progressive method for item selection, the Sympson and Hetter method with online and freeze procedure for item exposure control, and the multinomial model for content balancing can simultaneously maintain good measurement precision, item exposure control, content balance, test security, and pool usage. (Contains 3 tables and 2 figures.) |
| Abstractor: | As Provided |
| Number of References: | 43 |
| Entry Date: | 2012 |
| Accession Number: | EJ982803 |
| Database: | ERIC |
| Abstract: | In the human sciences, a common assumption is that latent traits have a hierarchical structure. Higher order item response theory models have been developed to account for this hierarchy. In this study, computerized adaptive testing (CAT) algorithms based on these kinds of models were implemented, and their performance under a variety of situations was examined using simulations. The results showed that the CAT algorithms were very effective. The progressive method for item selection, the Sympson and Hetter method with online and freeze procedure for item exposure control, and the multinomial model for content balancing can simultaneously maintain good measurement precision, item exposure control, content balance, test security, and pool usage. (Contains 3 tables and 2 figures.) |
|---|---|
| ISSN: | 0146-6216 |
| DOI: | 10.1177/0146621612459552 |
