Bayesian item response theory and latent dirichlet allocation applied to textual professor performance profiling

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dc.contributor.advisorAdvisor: Rosas, Harvey
dc.contributor.advisorCo-advisor: Montenegro, Álvaro
dc.contributor.authorJorquera Sandoval, Eduardo
dc.coverage.spatialValparaíso
dc.date.accessioned2024-08-07T17:19:42Z
dc.date.available2024-08-07T17:19:42Z
dc.date.issued2019
dc.description.abstractThe evaluation of teaching and the perception about the academic environment are only obtained through students. Measure the teachers’ performance and subject relevance has an increasing importance for universities and academic institutions since these evaluations are subjective. Thus, a natural question is: how to develope an unbiased measure through subjective answers? This thesis uses several statistical tools in order to measure professor performance and subject relevance. An strategic diagram is constructed to compare these latent variables. Item response theory (IRT) is used to propose a method to measure teachers’ performance and subject relevance, also Latent Dirichlet allocation (LDA) is used to model textual data, and clustered in order to profile professors using students’ comments.
dc.facultadFacultad de Ciencias
dc.identifier.urihttps://repositoriobibliotecas.uv.cl/handle/uvscl/14212
dc.language.isoen
dc.publisherUniversidad de Valparaíso
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/cl/
dc.subjectANALISIS BAYESIANO
dc.subjectDESEMPEÑO HUMANO
dc.subjectEVALUACION
dc.subjectENCUESTAS
dc.subjectESTUDIANTES
dc.titleBayesian item response theory and latent dirichlet allocation applied to textual professor performance profiling
dc.typeThesis
uv.catalogadorPJR CIEN
uv.codigo.barra00421930
uv.colectionTesis
uv.departamentoFacultad de Ciencias, Instituto de Estadística
uv.notageneralMagíster en Estadística. Universidad de Valparaíso. 2019.

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