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Evaluation of Student Performance through a Multidimensional Finite Mixture IRT Model.
Bacci, Silvia; Bartolucci, Francesco; Grilli, Leonardo; Rampichini, Carla.
Afiliação
  • Bacci S; a Department of Economics , University of Perugia (IT).
  • Bartolucci F; a Department of Economics , University of Perugia (IT).
  • Grilli L; b Department of Statistics, Computer Science, Applications "G. Parenti" , University of Florence (IT).
  • Rampichini C; b Department of Statistics, Computer Science, Applications "G. Parenti" , University of Florence (IT).
Multivariate Behav Res ; 52(6): 732-746, 2017.
Article em En | MEDLINE | ID: mdl-28952784
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Interpretação Estatística de Dados / Modelos Estatísticos / Desempenho Acadêmico Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male País/Região como assunto: Europa Idioma: En Revista: Multivariate Behav Res Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Interpretação Estatística de Dados / Modelos Estatísticos / Desempenho Acadêmico Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male País/Região como assunto: Europa Idioma: En Revista: Multivariate Behav Res Ano de publicação: 2017 Tipo de documento: Article