Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagem
Autor(a) principal: | |
---|---|
Data de Publicação: | 2019 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Repositório Institucional da Universidade Federal de Alagoas (UFAL) |
Texto Completo: | http://www.repositorio.ufal.br/handle/riufal/5547 |
Resumo: | The virtual learning environments (VLE) have been, over the years, an instrument in the dynamization of the teaching-learning process of distance education online. These are called Big Data, and these environments have a huge range of data. These data can be increased in potentially qualified information that, with the aid of technologies such as Learning Analytics (LA), stimulate the generation of relevant indicators for a diagnostic evaluation of teachers during the course of a given discipline, always seeking to elucidate better strategies to achieve the success of the student, consequently promoting an education with better quality. LA in conjunction with Educational Data Mining (EDM) techniques can represent a major breakthrough to resources already existing in the current VLE of higher education institutions, which by default are rather scarce and complex. This thesis identified the difficulties teachers had in assessing VLE, based on a methodology that they used in addition to the literature review and the Goal-Question-Metric (GQM) planning, also developed and evaluated an experiment carried out with teachers who work in distance education at higher education institutions, which were addressed tools that include the objectives of LA, including a new contribution called LAnalize, and validate these for the evaluation evaluation. The results, based on the objectives achieved, showed that teachers need adequate qualification to take advantage of the more sophisticated information and communication technologies (ICT), which managers (managers) have, however, without much assertiveness, motivation for the implantation of new tools in the VLE institutional and that there are tools of LA available in the VLE-Moodle for the diagnostic evaluation support to the profile of the teacher. The tools used to promote actions to achieve the purpose of the teaching evaluation practice in VLE through the LA were: Completion Progress (18.5%), Course Dedication (18.1%) and Level Up! (17.8%), followed by "evaluation / feedback" (13.0%) and "intervention" (12.0%) %). The tool developed, a plugin for LA called LAnalize, stood out among all the tools used in the experiment, being classified by the System Usability Scale (SUS) as excellent with the score of 91.1 points in the usability question, becoming a contribution for the VLE-Moodle community. |
id |
UFAL_42e75ce84e77db2abf3738b463acf1f9 |
---|---|
oai_identifier_str |
oai:www.repositorio.ufal.br:riufal/5547 |
network_acronym_str |
UFAL |
network_name_str |
Repositório Institucional da Universidade Federal de Alagoas (UFAL) |
repository_id_str |
|
spelling |
Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagemLearning analytics as support in the diagnostic evaluation of teachers in the virtual learning environmentLearning analyticsAmbiente virtual de aprendizagemEnsino pela internetAvaliação diagnósticaTecnologia da informação e da comunicaçãoVirtual Learning EnvironmentsInternet teachingDiagnostic EvaluationInformation and Communication TechnologiesOnline EducationCNPQ::CIENCIAS HUMANAS::EDUCACAOThe virtual learning environments (VLE) have been, over the years, an instrument in the dynamization of the teaching-learning process of distance education online. These are called Big Data, and these environments have a huge range of data. These data can be increased in potentially qualified information that, with the aid of technologies such as Learning Analytics (LA), stimulate the generation of relevant indicators for a diagnostic evaluation of teachers during the course of a given discipline, always seeking to elucidate better strategies to achieve the success of the student, consequently promoting an education with better quality. LA in conjunction with Educational Data Mining (EDM) techniques can represent a major breakthrough to resources already existing in the current VLE of higher education institutions, which by default are rather scarce and complex. This thesis identified the difficulties teachers had in assessing VLE, based on a methodology that they used in addition to the literature review and the Goal-Question-Metric (GQM) planning, also developed and evaluated an experiment carried out with teachers who work in distance education at higher education institutions, which were addressed tools that include the objectives of LA, including a new contribution called LAnalize, and validate these for the evaluation evaluation. The results, based on the objectives achieved, showed that teachers need adequate qualification to take advantage of the more sophisticated information and communication technologies (ICT), which managers (managers) have, however, without much assertiveness, motivation for the implantation of new tools in the VLE institutional and that there are tools of LA available in the VLE-Moodle for the diagnostic evaluation support to the profile of the teacher. The tools used to promote actions to achieve the purpose of the teaching evaluation practice in VLE through the LA were: Completion Progress (18.5%), Course Dedication (18.1%) and Level Up! (17.8%), followed by "evaluation / feedback" (13.0%) and "intervention" (12.0%) %). The tool developed, a plugin for LA called LAnalize, stood out among all the tools used in the experiment, being classified by the System Usability Scale (SUS) as excellent with the score of 91.1 points in the usability question, becoming a contribution for the VLE-Moodle community.FAPEAL - Fundação de Amparo à Pesquisa do Estado de AlagoasOs ambientes virtuais de aprendizagem (AVA) tem sido, ao longo dos anos, um instrumento na dinamização do processo de ensino-aprendizagem da educação a distância (EaD) online. Constituindo-se dos denominados Big Data, esses ambientes dispõem de uma enorme gama de dados. Esses dados podem avolumar-se em informações potencialmente qualificadas que com o auxílio de tecnologias como a Learning Analytics (LA) impulsionam a geração de relevantes indicadores para uma avaliação diagnóstica docente durante o percurso de uma determinada disciplina, buscando sempre elucidar melhores estratégias para alcançar o sucesso do discente, consequentemente promovendo uma educação com melhor qualidade. A LA em conjunto com técnicas de Educational Data Mining (EDM) pode representar um grande avanço aos recursos já existentes nos AVA atuais das instituições de ensino superior (IES), que de forma padrão são bastante escassos e complexos. Esta tese identificou as dificuldades docentes para avaliar nos AVA, a partir metodologia que utilizou além da revisão da literatura e o planejamento Goal- Question-Metric (GQM), desenvolveu e avaliou também um experimento realizado com docentes que atuam na EaD em IES, nas quais foram abordadas ferramentas que contemplam os objetivos de LA, incluindo um novo contributo denominado LAnalize, efetuando-se a validação destas para o apoio avaliativo docente. Os resultados, a partir dos objetivos atingidos, evidenciaram que os docentes necessitam de qualificação adequada para usufruir das tecnologias de informação e comunicação (TIC) mais sofisticadas, que os gestores (diretores) têm, porém sem muita assertividade, motivação para a implantação de novas ferramentas no AVA institucional e que existem ferramentas de LA disponíveis no AVA-Moodle para o apoio avaliativo diagnóstico ao perfil do docente. As ferramentas utilizadas que despontaram no tocante em promover ações para atingir o propósito da prática avaliativa docente no AVA através da LA foram: Completion Progress (18,5%), Course Dedication (18,1%) e Level Up! (17,8%), já as ações de LA com maiores graus de destaque foram: “monitoramento” (17,4%), seguido por “avaliação/feedback” (13,0%) e “intervenção” (12,0%). A ferramenta desenvolvida, um plugin para LA denominado LAnalize, se destacou entre todas as ferramentas utilizadas no experimento, sendo classificado pela System Usability Scale (SUS) como excelente com o score de 91,1 pontos no quesito de usabilidade, tornando-se um contributo para a comunidade do AVA-Moodle.Universidade Federal de AlagoasBrasilPrograma de Pós-Graduação em EducaçãoUFALMercado, Luís Paulo Leopoldohttp://lattes.cnpq.br/5780536667755396Brito, Patrick Henrique Da Silvahttp://lattes.cnpq.br/4155051332618408Pimentel, Fernando Silvio Cavalcantehttp://lattes.cnpq.br/3181078095367990Dantas, Anderson de Barroshttp://lattes.cnpq.br/5746362792333415Ramos, Jorge Luis Cavalcantihttp://lattes.cnpq.br/1438322656914569Serra, Kleber Cavalcantihttp://lattes.cnpq.br/3763135856142994Dias Júnior, Maurício Vieira2019-07-24T19:51:23Z2019-06-272019-07-24T19:51:23Z2019-05-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfDIAS JÚNIOR, Maurício Vieira. Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagem. 2019. 221 f. Tese (Doutorado em Educação) – Centro de Educação, Programa de Pós Graduação em Educação, Universidade Federal de Alagoas, Maceió, 2019.http://www.repositorio.ufal.br/handle/riufal/5547porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da Universidade Federal de Alagoas (UFAL)instname:Universidade Federal de Alagoas (UFAL)instacron:UFAL2019-07-24T19:51:23Zoai:www.repositorio.ufal.br:riufal/5547Repositório InstitucionalPUBhttp://www.repositorio.ufal.br/oai/requestri@sibi.ufal.bropendoar:2019-07-24T19:51:23Repositório Institucional da Universidade Federal de Alagoas (UFAL) - Universidade Federal de Alagoas (UFAL)false |
dc.title.none.fl_str_mv |
Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagem Learning analytics as support in the diagnostic evaluation of teachers in the virtual learning environment |
title |
Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagem |
spellingShingle |
Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagem Dias Júnior, Maurício Vieira Learning analytics Ambiente virtual de aprendizagem Ensino pela internet Avaliação diagnóstica Tecnologia da informação e da comunicação Virtual Learning Environments Internet teaching Diagnostic Evaluation Information and Communication Technologies Online Education CNPQ::CIENCIAS HUMANAS::EDUCACAO |
title_short |
Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagem |
title_full |
Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagem |
title_fullStr |
Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagem |
title_full_unstemmed |
Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagem |
title_sort |
Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagem |
author |
Dias Júnior, Maurício Vieira |
author_facet |
Dias Júnior, Maurício Vieira |
author_role |
author |
dc.contributor.none.fl_str_mv |
Mercado, Luís Paulo Leopoldo http://lattes.cnpq.br/5780536667755396 Brito, Patrick Henrique Da Silva http://lattes.cnpq.br/4155051332618408 Pimentel, Fernando Silvio Cavalcante http://lattes.cnpq.br/3181078095367990 Dantas, Anderson de Barros http://lattes.cnpq.br/5746362792333415 Ramos, Jorge Luis Cavalcanti http://lattes.cnpq.br/1438322656914569 Serra, Kleber Cavalcanti http://lattes.cnpq.br/3763135856142994 |
dc.contributor.author.fl_str_mv |
Dias Júnior, Maurício Vieira |
dc.subject.por.fl_str_mv |
Learning analytics Ambiente virtual de aprendizagem Ensino pela internet Avaliação diagnóstica Tecnologia da informação e da comunicação Virtual Learning Environments Internet teaching Diagnostic Evaluation Information and Communication Technologies Online Education CNPQ::CIENCIAS HUMANAS::EDUCACAO |
topic |
Learning analytics Ambiente virtual de aprendizagem Ensino pela internet Avaliação diagnóstica Tecnologia da informação e da comunicação Virtual Learning Environments Internet teaching Diagnostic Evaluation Information and Communication Technologies Online Education CNPQ::CIENCIAS HUMANAS::EDUCACAO |
description |
The virtual learning environments (VLE) have been, over the years, an instrument in the dynamization of the teaching-learning process of distance education online. These are called Big Data, and these environments have a huge range of data. These data can be increased in potentially qualified information that, with the aid of technologies such as Learning Analytics (LA), stimulate the generation of relevant indicators for a diagnostic evaluation of teachers during the course of a given discipline, always seeking to elucidate better strategies to achieve the success of the student, consequently promoting an education with better quality. LA in conjunction with Educational Data Mining (EDM) techniques can represent a major breakthrough to resources already existing in the current VLE of higher education institutions, which by default are rather scarce and complex. This thesis identified the difficulties teachers had in assessing VLE, based on a methodology that they used in addition to the literature review and the Goal-Question-Metric (GQM) planning, also developed and evaluated an experiment carried out with teachers who work in distance education at higher education institutions, which were addressed tools that include the objectives of LA, including a new contribution called LAnalize, and validate these for the evaluation evaluation. The results, based on the objectives achieved, showed that teachers need adequate qualification to take advantage of the more sophisticated information and communication technologies (ICT), which managers (managers) have, however, without much assertiveness, motivation for the implantation of new tools in the VLE institutional and that there are tools of LA available in the VLE-Moodle for the diagnostic evaluation support to the profile of the teacher. The tools used to promote actions to achieve the purpose of the teaching evaluation practice in VLE through the LA were: Completion Progress (18.5%), Course Dedication (18.1%) and Level Up! (17.8%), followed by "evaluation / feedback" (13.0%) and "intervention" (12.0%) %). The tool developed, a plugin for LA called LAnalize, stood out among all the tools used in the experiment, being classified by the System Usability Scale (SUS) as excellent with the score of 91.1 points in the usability question, becoming a contribution for the VLE-Moodle community. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-07-24T19:51:23Z 2019-06-27 2019-07-24T19:51:23Z 2019-05-10 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
DIAS JÚNIOR, Maurício Vieira. Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagem. 2019. 221 f. Tese (Doutorado em Educação) – Centro de Educação, Programa de Pós Graduação em Educação, Universidade Federal de Alagoas, Maceió, 2019. http://www.repositorio.ufal.br/handle/riufal/5547 |
identifier_str_mv |
DIAS JÚNIOR, Maurício Vieira. Learning analytics como apoio na avaliação diagnóstica dos docentes no ambiente virtual de aprendizagem. 2019. 221 f. Tese (Doutorado em Educação) – Centro de Educação, Programa de Pós Graduação em Educação, Universidade Federal de Alagoas, Maceió, 2019. |
url |
http://www.repositorio.ufal.br/handle/riufal/5547 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Alagoas Brasil Programa de Pós-Graduação em Educação UFAL |
publisher.none.fl_str_mv |
Universidade Federal de Alagoas Brasil Programa de Pós-Graduação em Educação UFAL |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da Universidade Federal de Alagoas (UFAL) instname:Universidade Federal de Alagoas (UFAL) instacron:UFAL |
instname_str |
Universidade Federal de Alagoas (UFAL) |
instacron_str |
UFAL |
institution |
UFAL |
reponame_str |
Repositório Institucional da Universidade Federal de Alagoas (UFAL) |
collection |
Repositório Institucional da Universidade Federal de Alagoas (UFAL) |
repository.name.fl_str_mv |
Repositório Institucional da Universidade Federal de Alagoas (UFAL) - Universidade Federal de Alagoas (UFAL) |
repository.mail.fl_str_mv |
ri@sibi.ufal.br |
_version_ |
1748233731533963264 |