Abstract
Mastery testing concerns the decision to classify a student as a master or as a nonmaster. In the previous chapter, adaptive mastery testing (AMT) using item response theory (IRT) and sequential mastery testing (SMT) using Bayesian decision theory were combined into an approach labeled adaptive sequential mastery testing (ASMT). This approach is based on the one-parameter logistic model (1PLM; Rasch, 1960) and three-parameter logistic model (3PLM; Birnbaum, 1968). In the present chapter, ASMT is applied to a multidimensional IRT (MIRT) model.
| Original language | English |
|---|---|
| Title of host publication | Elements of adaptive testing |
| Editors | Wim J. van der Linden, Cees A.W. Glas |
| Place of Publication | New York, NY |
| Publisher | Springer |
| Pages | 409-431 |
| ISBN (Electronic) | 978-0-387-85461-8 |
| ISBN (Print) | 978-0-387-85459-5 |
| DOIs | |
| Publication status | Published - 2010 |
Keywords
- Loss function
- Item parameter
- Computerize adaptive testing (CAT)
- Computer adaptive testing
- Latent trait model