The practical application of Optimal Appropriateness Measurement on empirical data using rasch models

Abstract

Optimal Appropriateness Measurement (OAM) is a general statistical method for the identification of examinees whose test scores might not be a valid indicator of their true latent ability or trait. The method is statistically very powerful and it pinpoints towards the direction of the suspected aberrance instead of simply identifying that a specific response pattern is, in some way, aberrant. The method has been traditionally used with multiparameter IRMs for the identification of examinees with spuriously low and high scores. This article presents the practical application of the method, using Rasch models, in the context of a large-scale activity which aimed to provide secondary education schools with feedback about their students' performance on a high-stakes University entrance science test. Although researchers in the past claimed that OAM was not ready to be routinely used in practical settings, this article maintains that the practical use of OAM to answer specific educationally meaningful questions is feasible.