A Network approach to deal with the problem of examinee choice under item response theory

Detalhes bibliográficos
Ano de defesa: 2016
Autor(a) principal: Carolina Silva Pena
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
UFMG
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/1843/BUBD-AHSKQF
Resumo: In a typical questionnaire testing situation, the examinees are not allowed to choose which items they would rather answer. The main reason is a technical issue in obtaining satisfactory statistical estimates of examinees' abilities and items' difficulties. This paper introduces a new Item Response Theory (IRT) model that incorporates information from a novel representation of the questionnaire data, using network analysis. The questionnaire data set is coded as layers, the items are coded as nodes and the selected items are connected by edges. The new proposed Item Response Theory (IRT) model incorporates networkinformation using Bayesian estimation. Several simulation studies in which examinees are allowed to select a subset of items were performed. Results show substantial improvements in the parameters' recovery over the standard model. To the best of our knowledge, this is the first proposal to obtaining satisfactory IRT statistical estimates in some critical scenarios reported in literature.