Um modelo de transferência de tecnologias para a educação básica para avaliação de alunos com sinais do transtorno do espectro autista e deficiência intelectual

Detalhes bibliográficos
Ano de defesa: 2018
Autor(a) principal: Suriano, Raquel lattes
Orientador(a): Teixeira, Maria Cristina Triguero Veloz lattes
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Presbiteriana Mackenzie
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Área do conhecimento CNPq:
Link de acesso: http://dspace.mackenzie.br/handle/10899/22740
Resumo: Research within Brazilian context report difficulties that educators and management staff face to make sure that students with educational and developmental delay complaints are properly assessed and receive required educational intervention. The general objective of this project was to develop two standardized frameworks of assessment of basic education students with indicators of Autistic Spectrum Disorder (ASD) and Intellectual Disability (ID) through the use of a Big Data environment. The specific objectives were: a) to provide tools for teachers and management staff to use standardized assessment procedures for triage of students suspected of having a disorder; b) to identify in the students indicators compatible with TEA and DI according to the instruments of the models; c) to verify indicators of sensitivity to standardized triage procedures and cognitive and behavioral assessment considering the number of false positives. The sample was composed of: a) 16 psycho-pedagogues that work on the 16 sectors in which the educational network is divided to cover schools of each sector; b) 10 professionals of the Interdisciplinary Department for Inclusion (IDI) that support the process of educational inclusion; c) 2 teachers of the 2nd and 4th grades of elementary school of each sector (one from the 2nd grade, one from the 4th grade), 32 teachers in total; d) their respective students that presented signs of ASD and ID during the period of this project; e) parents of these students. Each classroom had an average of 25 to 30 students. The tools for data collection were: a) two checklists to identify signs of ID and ASD; b) Wechsler Abbreviated Scale of Intelligence (WASI); c) Brief Problems Monitor, parents and teachers from; d) Autism Behavior Inventory; e) guidebook with orientations to deal with students with signs of ID and/or ASD in the classroom. To assess the efficacy of the framework, false positives were calculated according to the diagnostic confirmation or not of the suspected ID or ASD. Descriptive analyses were made to characterize the sample of students, and predictive analyses through Data Mining techniques were carried out to verify the indicators that are most sensitive to the definition of complaints compatible with the disorders. The main results show that for ID indicators, considering the cognitive control and intellectual functioning skills assessed through WASI, 72.22% of the sample presented indicators of low intellectual functioning. This corresponds to 27.78% of false positives that tested normal and below average according to WASI. On the other hand, since it was not possible to reach a diagnosis for any of the students suspected of having ASD, the indicators of false positives corresponded to 100% of the sample. The signs that seemed most distinctive for the suspicion of ASD were linked to deficits in communication and social interaction. For ID cases, such signs were social commitments in daily life. After the data collection, the research enabled the creation of a Big Data environment for data analysis and decision-making for the identification of students suspected of having neurodevelopmental disorders compatible with ASD and ID. Teachers and management staff, actors of the process, were able to employ assessment procedures for students suspected of having disorders, thus displaying a more effective use of public resources.
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spelling Suriano, Raquelhttp://lattes.cnpq.br/1500695593391363Teixeira, Maria Cristina Triguero Velozhttp://lattes.cnpq.br/89968910352347752018-04-09T16:50:07Z2020-03-19T15:20:37Z2020-03-19T15:20:37Z2018-02-27SURIANO, Raquel. Um modelo de transferência de tecnologias para a educação básica para avaliação de alunos com sinais do transtorno do espectro autista e deficiência intelectual. 2018. 78 f. Dissertação (Distúrbios do Desenvolvimento) - Universidade Presbiteriana Mackenzie, São Paulo.http://dspace.mackenzie.br/handle/10899/22740Research within Brazilian context report difficulties that educators and management staff face to make sure that students with educational and developmental delay complaints are properly assessed and receive required educational intervention. The general objective of this project was to develop two standardized frameworks of assessment of basic education students with indicators of Autistic Spectrum Disorder (ASD) and Intellectual Disability (ID) through the use of a Big Data environment. The specific objectives were: a) to provide tools for teachers and management staff to use standardized assessment procedures for triage of students suspected of having a disorder; b) to identify in the students indicators compatible with TEA and DI according to the instruments of the models; c) to verify indicators of sensitivity to standardized triage procedures and cognitive and behavioral assessment considering the number of false positives. The sample was composed of: a) 16 psycho-pedagogues that work on the 16 sectors in which the educational network is divided to cover schools of each sector; b) 10 professionals of the Interdisciplinary Department for Inclusion (IDI) that support the process of educational inclusion; c) 2 teachers of the 2nd and 4th grades of elementary school of each sector (one from the 2nd grade, one from the 4th grade), 32 teachers in total; d) their respective students that presented signs of ASD and ID during the period of this project; e) parents of these students. Each classroom had an average of 25 to 30 students. The tools for data collection were: a) two checklists to identify signs of ID and ASD; b) Wechsler Abbreviated Scale of Intelligence (WASI); c) Brief Problems Monitor, parents and teachers from; d) Autism Behavior Inventory; e) guidebook with orientations to deal with students with signs of ID and/or ASD in the classroom. To assess the efficacy of the framework, false positives were calculated according to the diagnostic confirmation or not of the suspected ID or ASD. Descriptive analyses were made to characterize the sample of students, and predictive analyses through Data Mining techniques were carried out to verify the indicators that are most sensitive to the definition of complaints compatible with the disorders. The main results show that for ID indicators, considering the cognitive control and intellectual functioning skills assessed through WASI, 72.22% of the sample presented indicators of low intellectual functioning. This corresponds to 27.78% of false positives that tested normal and below average according to WASI. On the other hand, since it was not possible to reach a diagnosis for any of the students suspected of having ASD, the indicators of false positives corresponded to 100% of the sample. The signs that seemed most distinctive for the suspicion of ASD were linked to deficits in communication and social interaction. For ID cases, such signs were social commitments in daily life. After the data collection, the research enabled the creation of a Big Data environment for data analysis and decision-making for the identification of students suspected of having neurodevelopmental disorders compatible with ASD and ID. Teachers and management staff, actors of the process, were able to employ assessment procedures for students suspected of having disorders, thus displaying a more effective use of public resources.Estudos no cenário educacional brasileiro reportam as dificuldades que educadores e equipes gestoras enfrentam para garantir que os alunos com queixas acadêmicas e de atraso de desenvolvimento tenham as devidas avaliações e intervenções educacionais necessárias. O objetivo geral do projeto foi desenvolver, para Educação Básica, dois modelos padronizados de avaliação de alunos com indicadores de Transformo do Espectro Autista (TEA) e Deficiência Intelectual (DI) mediante a utilização de um ambiente Big Data. Os objetivos específicos foram: a) Instrumentalizar professores e gestores educacionais no uso de procedimentos adronizados de avaliação para a triagem de alunos com essas suspeitas; b) Identificar nos alunos indicadores compatíveis com TEA e DI em função dos instrumentos dos modelos; c) Verificar indicadores de sensibilidade dos procedimentos padronizados de triagem e avaliação cognitiva e comportamental em função do número de casos falsos positivos. A amostra foi composta por 16 psicopedagogos que acompanham os 16 setores em que a rede educacional se divide para atender as escolas de cada setor; b) 10 profissionais do Departamento Interdisciplinar de Apoio à Inclusão (DIAI) que auxiliam o processo de inclusão escolar na rede educacional; c) Dois professores de salas de aula de 2º e 4º ano do Ensino Fundamental I de cada setor (01 professor de sala de aula de 2º ano e 01 professor de sala de aula de 4º ano), totalizando 32 professores; d) Os respectivos alunos desses professores que apresentavam sinais de TEA e de DI no período que abrangeu a execução do projeto; e) Pais dos respectivos alunos. Cada sala de aula tinha em média entre 25 a 30 alunos. Os instrumentos para coleta de dados foram: a) Dois checklists para identificação de sinais de DI e de TEA; b) Escala Wechsler abreviada de inteligência; c) Breve Monitor de Problemas-Formulário para Professores e para Pais; d) Inventário de Comportamentos Autísticos; e) Roteiro de orientações de manejo de alunos com sinais e/ou TEA em sala de aula. Para avaliar a efetividade do modelo foram feitos cálculos do número de falsos positivos em função da confirmação diagnóstica ou não da suspeita de DI e TEA. Foram conduzidas análises descritivas para caracterização da amostra de alunos e análises preditivas mediante o uso de técnicas de Mineração de Dados que pudessem verificar os indicadores que são mais sensíveis na definição das queixas compatíveis com os transtornos. Os principais resultados apontaram no caso dos sinais de DI que, considerando o domínio cognitivo, avaliado a partir de habilidades de funcionamento intelectual mediante a WASI, 72,22% da amostra apresenta indicadores de rebaixamento intelectual o que corresponde a um índice de 27,78% de casos falsos positivos que classificaram normal e médio inferior de acordo com a WASI. Diferentemente, como não foi possível efetuar diagnóstico em nenhum dos alunos com o levantamento da suspeita de TEA, o índice de casos falsos positivos correspondeu a 100% da amostra. Os sinais que se mostraram mais discriminativos para o levantamento de suspeita de TEA foram vinculados a déficits na comunicação e interação social. Nos casos da DI foram os comprometimentos sociais na vida diária. O estudo permitiu gerar, após as coletas, um ambiente Big Data para as análises de dados e tomadas de decisão para identificação de alunos com suspeita de transtornos do neurodesenvolvimento compatíveis com DI e TEA, os professores e gestores, atores do processo puderam usar os procedimentos de avaliação dos alunos que apresentam as suspeitas, mostrando a possibilidade de um uso mais eficaz dos recursos públicos.Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorapplication/pdfporUniversidade Presbiteriana Mackenziehttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesstranstorno do espectro autistadeficiência intelectualrede pública de ensinoprofessorespaisCNPQ::CIENCIAS HUMANAS::PSICOLOGIA::PSICOLOGIA EXPERIMENTAL::PROCESSOS COGNITIVOS E ATENCIONAISUm modelo de transferência de tecnologias para a educação básica para avaliação de alunos com sinais do transtorno do espectro autista e deficiência intelectualinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://tede.mackenzie.br/jspui/retrieve/16060/Raquel%20Suriano.pdf.jpgautistic spectrum disorderintellectual disabilitypublic educationteachersparentsreponame:Repositório Digital do Mackenzieinstname:Universidade Presbiteriana Mackenzie (MACKENZIE)instacron:MACKENZIERocha, Marina Monzani dahttp://lattes.cnpq.br/6765747992813196Gioia, Paula Suzanahttp://lattes.cnpq.br/5020508534795298BrasilCentro de Ciências Biológicas e da Saúde (CCBS)UPMDistúrbios do DesenvolvimentoORIGINALRaquel Suriano.pdfRaquel Suriano.pdfapplication/pdf1171014https://dspace.mackenzie.br/bitstreams/144a52f8-219d-4e99-8b18-fa4344702d5f/downloadb4465ce34dce6d03b729af7b33949e72MD51trueAnonymousREADTEXTRaquel Suriano.pdf.txtRaquel Suriano.pdf.txtExtracted texttext/plain139512https://dspace.mackenzie.br/bitstreams/39351082-38f0-4d3d-bb35-7fc024d6000f/download523a4a334b2684b68e6a36888e145b9fMD52falseAnonymousREADTHUMBNAILRaquel Suriano.pdf.jpgRaquel Suriano.pdf.jpgGenerated Thumbnailimage/jpeg1242https://dspace.mackenzie.br/bitstreams/50eb2901-7831-4297-9f45-63af086ed4fd/download8dacda4a6e6490153736d77ca63901dfMD53falseAnonymousREAD10899/227402022-03-14T19:46:31.413Zhttp://creativecommons.org/licenses/by-nc-nd/4.0/Acesso Abertoopen.accessoai:dspace.mackenzie.br:10899/22740https://dspace.mackenzie.brBiblioteca Digital de Teses e Dissertaçõeshttp://tede.mackenzie.br/jspui/PRIhttps://adelpha-api.mackenzie.br/server/oai/repositorio@mackenzie.br||paola.damato@mackenzie.bropendoar:102772022-03-14T19:46:31Repositório Digital do Mackenzie - Universidade Presbiteriana Mackenzie (MACKENZIE)false
dc.title.por.fl_str_mv Um modelo de transferência de tecnologias para a educação básica para avaliação de alunos com sinais do transtorno do espectro autista e deficiência intelectual
title Um modelo de transferência de tecnologias para a educação básica para avaliação de alunos com sinais do transtorno do espectro autista e deficiência intelectual
spellingShingle Um modelo de transferência de tecnologias para a educação básica para avaliação de alunos com sinais do transtorno do espectro autista e deficiência intelectual
Suriano, Raquel
transtorno do espectro autista
deficiência intelectual
rede pública de ensino
professores
pais
CNPQ::CIENCIAS HUMANAS::PSICOLOGIA::PSICOLOGIA EXPERIMENTAL::PROCESSOS COGNITIVOS E ATENCIONAIS
title_short Um modelo de transferência de tecnologias para a educação básica para avaliação de alunos com sinais do transtorno do espectro autista e deficiência intelectual
title_full Um modelo de transferência de tecnologias para a educação básica para avaliação de alunos com sinais do transtorno do espectro autista e deficiência intelectual
title_fullStr Um modelo de transferência de tecnologias para a educação básica para avaliação de alunos com sinais do transtorno do espectro autista e deficiência intelectual
title_full_unstemmed Um modelo de transferência de tecnologias para a educação básica para avaliação de alunos com sinais do transtorno do espectro autista e deficiência intelectual
title_sort Um modelo de transferência de tecnologias para a educação básica para avaliação de alunos com sinais do transtorno do espectro autista e deficiência intelectual
author Suriano, Raquel
author_facet Suriano, Raquel
author_role author
dc.contributor.author.fl_str_mv Suriano, Raquel
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/1500695593391363
dc.contributor.advisor1.fl_str_mv Teixeira, Maria Cristina Triguero Veloz
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/8996891035234775
contributor_str_mv Teixeira, Maria Cristina Triguero Veloz
dc.subject.por.fl_str_mv transtorno do espectro autista
deficiência intelectual
rede pública de ensino
professores
pais
topic transtorno do espectro autista
deficiência intelectual
rede pública de ensino
professores
pais
CNPQ::CIENCIAS HUMANAS::PSICOLOGIA::PSICOLOGIA EXPERIMENTAL::PROCESSOS COGNITIVOS E ATENCIONAIS
dc.subject.cnpq.fl_str_mv CNPQ::CIENCIAS HUMANAS::PSICOLOGIA::PSICOLOGIA EXPERIMENTAL::PROCESSOS COGNITIVOS E ATENCIONAIS
description Research within Brazilian context report difficulties that educators and management staff face to make sure that students with educational and developmental delay complaints are properly assessed and receive required educational intervention. The general objective of this project was to develop two standardized frameworks of assessment of basic education students with indicators of Autistic Spectrum Disorder (ASD) and Intellectual Disability (ID) through the use of a Big Data environment. The specific objectives were: a) to provide tools for teachers and management staff to use standardized assessment procedures for triage of students suspected of having a disorder; b) to identify in the students indicators compatible with TEA and DI according to the instruments of the models; c) to verify indicators of sensitivity to standardized triage procedures and cognitive and behavioral assessment considering the number of false positives. The sample was composed of: a) 16 psycho-pedagogues that work on the 16 sectors in which the educational network is divided to cover schools of each sector; b) 10 professionals of the Interdisciplinary Department for Inclusion (IDI) that support the process of educational inclusion; c) 2 teachers of the 2nd and 4th grades of elementary school of each sector (one from the 2nd grade, one from the 4th grade), 32 teachers in total; d) their respective students that presented signs of ASD and ID during the period of this project; e) parents of these students. Each classroom had an average of 25 to 30 students. The tools for data collection were: a) two checklists to identify signs of ID and ASD; b) Wechsler Abbreviated Scale of Intelligence (WASI); c) Brief Problems Monitor, parents and teachers from; d) Autism Behavior Inventory; e) guidebook with orientations to deal with students with signs of ID and/or ASD in the classroom. To assess the efficacy of the framework, false positives were calculated according to the diagnostic confirmation or not of the suspected ID or ASD. Descriptive analyses were made to characterize the sample of students, and predictive analyses through Data Mining techniques were carried out to verify the indicators that are most sensitive to the definition of complaints compatible with the disorders. The main results show that for ID indicators, considering the cognitive control and intellectual functioning skills assessed through WASI, 72.22% of the sample presented indicators of low intellectual functioning. This corresponds to 27.78% of false positives that tested normal and below average according to WASI. On the other hand, since it was not possible to reach a diagnosis for any of the students suspected of having ASD, the indicators of false positives corresponded to 100% of the sample. The signs that seemed most distinctive for the suspicion of ASD were linked to deficits in communication and social interaction. For ID cases, such signs were social commitments in daily life. After the data collection, the research enabled the creation of a Big Data environment for data analysis and decision-making for the identification of students suspected of having neurodevelopmental disorders compatible with ASD and ID. Teachers and management staff, actors of the process, were able to employ assessment procedures for students suspected of having disorders, thus displaying a more effective use of public resources.
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