Evaluation of Student Performance through a Multidimensional Finite Mixture IRT Model. (2nd November 2017)

• Record Type: Journal Article
• Authors: Bacci, Silvia; Bartolucci, Francesco; Grilli, Leonardo; Rampichini, Carla
• Is Part Of: Multivariate behavioral research. Volume 52:Number 6(2017)
• Page Start: 732
• Page End: 746
• Publication Date: 2017-11-02
• Subjects: Education -- latent class model -- nonignorable missing responses -- ordinal responses -- within-item multidimensionality; Psychometrics -- Periodicals; Psychology, Experimental -- Periodicals; Psychology, Experimental; Psychometrics; Periodicals; 150.15195
• DOI: 10.1080/00273171.2017.1361803
• Languages: English
• ISSNs: 0027-3171

Abstract

ABSTRACT: In the Italian academic system, a student can enroll for an exam immediately after the end of the teaching period or can postpone it; in this second case the exam result is missing. We propose an approach for the evaluation of a student performance throughout the course of study, accounting also for nonattempted exams. The approach is based on an item response theory model that includes two discrete latent variables representing student performance and priority in selecting the exams to take. We explicitly account for nonignorable missing observations as the indicators of attempted exams also contribute to measure the performance (within-item multidimensionality). The model also allows for individual covariates in its structural part.