A Use of the Information Function in Tailored Testing

Abstract

Several important and useful implications in latent trait theory, with direct implications for individualized adaptive or tailored testing, are pointed out. A way of using the information function in tailored testing in connection with the standard error of estimation of the ability level using maximum likelihood estimation is suggested. It is emphasized that the standard error of estimation should be considered as the major index of dependability, as opposed to the reliability of a test. The concept of weak parallel forms is expanded to testing procedures in which different sets of items are presented to different examinees. Examples are given. Researchers have tended to use latent trait theory rather than classical test theory in research on individualized adaptive or tailored testing. This is quite natural, since latent trait theory has definite merits over classical test theory in many crucial matters. Because of the lack of opportunities to really learn the theory, however, these researchers tend to overlook some important implications in latent trait theory. As a result, its full use has not yet materialized. Not only are information functions seldom used to maximum advantage, but also those who have tried to use latent trait theory still use some popular concepts in classical test theory, such as reliability. expanded to testing procedures in which different sets of items are presented to different examinees. Examples are given. In this paper, the author points out some important implications in latent trait theory which are not fully understood and appreciated among researchers, and gives some practical suggestions for its use