Modeling of the growth of learning in the early years with longitudinal data of GERES research

Detalhes bibliográficos
Autor(a) principal: Brooke, Nigel
Data de Publicação: 2014
Outros Autores: Fernandes, Neimar da Silva, Miranda, Isabela Pagani Heringer de, Soares, Tufi Machado
Tipo de documento: Artigo
Idioma: por
Título da fonte: Educação e Pesquisa
Texto Completo: https://www.revistas.usp.br/ep/article/view/81869
Resumo: This article compares two value-added approaches to data from the longitudinal education survey called Estudo Longitudinal da Geração Escolar 2005 (GERES - Longitudinal Study of 2005 School Generation), which followed a cohort of students from more than 300 public and private schools over the first four years of primary education. Both approaches use hierarchical linear models, allowing the natural grouping of educational data from three levels: student, class and school. The first value-added approach builds models whose dependent variable is the student proficiency in each year evaluated. With a separate model for each year, it is possible to detect factors of the student, class and school associated with student performance. The second approach creates models to show the effect of the covariates of student, class and school on progress curves of proficiency throughout the study period. When comparing the two types of value-added models, the first one was the most efficient in diagnosing the effects of the environment and the teacher's pedagogical practice, but only in certain grades. The second type of model was able to identify progress curves of proficiency of different formats according to certain characteristics of schools and students, but was less sensitive to identify variables associated with the group formation process and the teacher's pedagogical practice. The two types of value-added models offer indications of differentiated learning processes for the disciplines of Portuguese and Mathematics, which deserve further study.
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spelling Modeling of the growth of learning in the early years with longitudinal data of GERES research Modelagem do crescimento da aprendizagem nos anos iniciais com dados longitudinais da pesquisa GERES This article compares two value-added approaches to data from the longitudinal education survey called Estudo Longitudinal da Geração Escolar 2005 (GERES - Longitudinal Study of 2005 School Generation), which followed a cohort of students from more than 300 public and private schools over the first four years of primary education. Both approaches use hierarchical linear models, allowing the natural grouping of educational data from three levels: student, class and school. The first value-added approach builds models whose dependent variable is the student proficiency in each year evaluated. With a separate model for each year, it is possible to detect factors of the student, class and school associated with student performance. The second approach creates models to show the effect of the covariates of student, class and school on progress curves of proficiency throughout the study period. When comparing the two types of value-added models, the first one was the most efficient in diagnosing the effects of the environment and the teacher's pedagogical practice, but only in certain grades. The second type of model was able to identify progress curves of proficiency of different formats according to certain characteristics of schools and students, but was less sensitive to identify variables associated with the group formation process and the teacher's pedagogical practice. The two types of value-added models offer indications of differentiated learning processes for the disciplines of Portuguese and Mathematics, which deserve further study. Este artigo compara duas abordagens de valor agregado para dados oriundos do survey educacional de recorte longitudinal, chamado GERES - Estudo Longitudinal da Geração Escolar 2005, que acompanhou uma coorte de alunos de mais de 300 escolas públicas e privadas ao longo dos primeiros quatro anos do Ensino Fundamental. Ambas as abordagens utilizam modelos lineares hierárquicos, permitindo o agrupamento natural dos dados educacionais provenientes dos três níveis: aluno, turma e escola. Na primeira abordagem de valor agregado, constroem-se modelos cuja variável dependente é a proficiência do aluno em cada ano avaliado. Com um modelo distinto para cada ano é possível detectar fatores do aluno, da turma e da escola associados ao desempenho dos alunos. A segunda abordagem cria modelos para mostrar o efeito das covariáveis de aluno, turma e escola nas curvas de evolução da proficiência ao longo do período do estudo. Quando comparados os dois tipos de modelos de valor agregado, o primeiro foi o mais eficiente em diagnosticar os efeitos do ambiente e da prática pedagógica do professor, mas somente em determinados anos. Já o segundo tipo de modelo foi capaz de identificar curvas de evolução de proficiência de formatos distintos de acordo com determinadas características das escolas e dos alunos, mas foi menos sensível na identificação de variáveis associadas ao processo de formação de grupos e à prática pedagógica do professor. Os dois tipos de modelos de valor agregado oferecem indicações de processos de aprendizagem diferenciados para as disciplinas Língua Portuguesa e Matemática que mereceriam estudos adicionais. Universidade de São Paulo. Faculdade de Educação2014-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/ep/article/view/8186910.1590/S1517-97022014000100006Educação e Pesquisa; v. 40 n. 1 (2014); 77-94Educação e Pesquisa; Vol. 40 No. 1 (2014); 77-94Educação e Pesquisa; Vol. 40 Núm. 1 (2014); 77-941678-46341517-9702reponame:Educação e Pesquisainstname:Universidade de São Paulo (USP)instacron:USPporhttps://www.revistas.usp.br/ep/article/view/81869/85146Copyright (c) 2017 Educação e Pesquisainfo:eu-repo/semantics/openAccessBrooke, NigelFernandes, Neimar da SilvaMiranda, Isabela Pagani Heringer deSoares, Tufi Machado2014-06-25T19:12:15Zoai:revistas.usp.br:article/81869Revistahttps://www.revistas.usp.br/ep/indexPUBhttps://www.revistas.usp.br/ep/oai||revedu@usp.br1678-46341517-9702opendoar:2014-06-25T19:12:15Educação e Pesquisa - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Modeling of the growth of learning in the early years with longitudinal data of GERES research
Modelagem do crescimento da aprendizagem nos anos iniciais com dados longitudinais da pesquisa GERES
title Modeling of the growth of learning in the early years with longitudinal data of GERES research
spellingShingle Modeling of the growth of learning in the early years with longitudinal data of GERES research
Brooke, Nigel
title_short Modeling of the growth of learning in the early years with longitudinal data of GERES research
title_full Modeling of the growth of learning in the early years with longitudinal data of GERES research
title_fullStr Modeling of the growth of learning in the early years with longitudinal data of GERES research
title_full_unstemmed Modeling of the growth of learning in the early years with longitudinal data of GERES research
title_sort Modeling of the growth of learning in the early years with longitudinal data of GERES research
author Brooke, Nigel
author_facet Brooke, Nigel
Fernandes, Neimar da Silva
Miranda, Isabela Pagani Heringer de
Soares, Tufi Machado
author_role author
author2 Fernandes, Neimar da Silva
Miranda, Isabela Pagani Heringer de
Soares, Tufi Machado
author2_role author
author
author
dc.contributor.author.fl_str_mv Brooke, Nigel
Fernandes, Neimar da Silva
Miranda, Isabela Pagani Heringer de
Soares, Tufi Machado
description This article compares two value-added approaches to data from the longitudinal education survey called Estudo Longitudinal da Geração Escolar 2005 (GERES - Longitudinal Study of 2005 School Generation), which followed a cohort of students from more than 300 public and private schools over the first four years of primary education. Both approaches use hierarchical linear models, allowing the natural grouping of educational data from three levels: student, class and school. The first value-added approach builds models whose dependent variable is the student proficiency in each year evaluated. With a separate model for each year, it is possible to detect factors of the student, class and school associated with student performance. The second approach creates models to show the effect of the covariates of student, class and school on progress curves of proficiency throughout the study period. When comparing the two types of value-added models, the first one was the most efficient in diagnosing the effects of the environment and the teacher's pedagogical practice, but only in certain grades. The second type of model was able to identify progress curves of proficiency of different formats according to certain characteristics of schools and students, but was less sensitive to identify variables associated with the group formation process and the teacher's pedagogical practice. The two types of value-added models offer indications of differentiated learning processes for the disciplines of Portuguese and Mathematics, which deserve further study.
publishDate 2014
dc.date.none.fl_str_mv 2014-03-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/ep/article/view/81869
10.1590/S1517-97022014000100006
url https://www.revistas.usp.br/ep/article/view/81869
identifier_str_mv 10.1590/S1517-97022014000100006
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://www.revistas.usp.br/ep/article/view/81869/85146
dc.rights.driver.fl_str_mv Copyright (c) 2017 Educação e Pesquisa
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2017 Educação e Pesquisa
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade de São Paulo. Faculdade de Educação
publisher.none.fl_str_mv Universidade de São Paulo. Faculdade de Educação
dc.source.none.fl_str_mv Educação e Pesquisa; v. 40 n. 1 (2014); 77-94
Educação e Pesquisa; Vol. 40 No. 1 (2014); 77-94
Educação e Pesquisa; Vol. 40 Núm. 1 (2014); 77-94
1678-4634
1517-9702
reponame:Educação e Pesquisa
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Educação e Pesquisa
collection Educação e Pesquisa
repository.name.fl_str_mv Educação e Pesquisa - Universidade de São Paulo (USP)
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