Computer Adaptive Multistage Testing: Practical Issues, Challenges and Principles
Abstract
The purpose of many test in
the educational and psychological measurement is to measure test takers’ latent
trait scores from responses given to a set of items. Over the years, this has
been done by traditional methods (paper and pencil tests). However, compared to
other test administration models (e.g., adaptive testing), traditional methods
are extensively criticized in terms of producing low measurement accuracy and
long test length. Adaptive testing has been proposed to overcome these
problems. There are two popular adaptive testing approaches. These are
computerized adaptive testing (CAT) and computer adaptive multistage testing
(ca-MST). The former is a
well-known approach that has been predominantly used in this field. We
believe that researchers and practitioners are fairly familiar with many
aspects of CAT because it has more than a hundred years of history. However,
the same thing is not true for the latter one. Since ca-MST is relatively new,
many researchers are not familiar with features of it. The purpose of this
study is to closely examine the characteristics of ca-MST, including its
working principle, the adaptation procedure called the routing method, test
assembly, and scoring, and provide an overview to researchers, with the aim of
drawing researchers’ attention to ca-MST and encouraging them to contribute to
the research in this area. The books, software and future work for ca-MST are
also discussed.
References
- Barrada, J. R., Olea, J., Ponsoda, V., & Abad, F. J. (2008). Incorporating randomness to the Fisher information for improving item exposure control in CATS. British Journal of Mathematical and Statistical Psychology, 61, 493-513.
Abstract
References
- Barrada, J. R., Olea, J., Ponsoda, V., & Abad, F. J. (2008). Incorporating randomness to the Fisher information for improving item exposure control in CATS. British Journal of Mathematical and Statistical Psychology, 61, 493-513.