Multidimensional Versus Unidimensional Models for Ability Testing

Abstract

Over last few years the need for an objective way of evaluating student performance has rapidly increased due to the growing call for the evaluation of tests administered at the end of a teaching process and during the guidance phases. Performance evaluation can be achieved busing the Item Response Theory (IRT) approach. In this work we compare the performance of an IRT model defined first on a multidimensional ability space and then on a unidimensional one. The aim of the comparison is to assess the results obtained in the two situations through a simulation study in terms of student classification based on ability estimates. The comparison is made using the two-parameter model defined within the more general framework of the Generalized Linear Latent Variable Models (GLLVM) since it allows the inclusion of more than one ability (latent variables). The simulation highlights that the importance of the dimensionality of the ability space increases when the number of items referring to more than one ability increases.