Um modelo computacional de apoio à análise da opinião de alunos sobre práticas docentes por meio da mineração de dados educacionais

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dc.contributor.advisorSilveira, Ismar Frango
dc.contributor.advisor1Latteshttp://lattes.cnpq.br/3894359521286830por
dc.contributor.authorSantos, Fábio de Paula
dc.creator.Latteshttp://lattes.cnpq.br/5929658408093646por
dc.date.accessioned2020-10-29T12:46:30Z
dc.date.accessioned2020-12-07T15:07:30Z
dc.date.available2020-12-07T15:07:30Z
dc.date.issued2017-04-27
dc.description.abstractThe Institutional Teacher’s Evaluation besides being a legal need in higher education is an important moment for any Educational Institution. Traditionally, questionnaires with closed answer questions are used for this purpose and many times the evaluation is left to a secondary place. This work proposes a computational model based in machine learning techniques and Sentiment Analysis that allows increasing the scope of this evaluation when allowing the use of open and textual questions. The application of these techniques in Educational Data Mining context provides basis to decision-making based on the students’ opinions. For this purpose, as proof of concept, a mining of a student’s opinion survey from a Vocational High School in Brazil was held and categorized their sentiments as positive or negative in relation to their lecturers’ techniques with supervised machine learning approach. This model also contemplates clustering analysis to find categories of analysis of student opinions through an unsupervised Learning Machine model. As a conclusion it was proven that the use of tools for textual analysis of open questions is possible and it to speeds up the decision-making of institutional evaluations.eng
dc.description.sponsorshipInstituto Federal de Educação, Ciência e Tecnologia de São Paulopor
dc.description.sponsorshipUniversidade Presbiteriana Mackenziepor
dc.formatapplication/pdf*
dc.identifier.citationSANTOS, Fábio de Paula. Um modelo computacional de apoio à análise da opinião de alunos sobre práticas docentes por meio da mineração de dados educacionais. 2017. 115 f. Tese (Engenharia Elétrica) - Universidade Presbiteriana Mackenzie, São Paulo, 2017.por
dc.identifier.urihttp://dspace.mackenzie.br/handle/10899/26515
dc.keywordseducational data miningeng
dc.keywordslearning machineseng
dc.keywordssentiment analysiseng
dc.keywordsinstitutional evaluationeng
dc.languageporpor
dc.publisherUniversidade Presbiteriana Mackenziepor
dc.rightsAcesso Abertopor
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectmineração de dados educacionaispor
dc.subjectaprendizado de máquinapor
dc.subjectanálise de sentimentospor
dc.subjectavaliação institucional docentepor
dc.subject.cnpqCNPQ::CIENCIAS EXATAS E DA TERRApor
dc.subject.cnpqCNPQ::LINGUISTICA, LETRAS E ARTES::LINGUISTICApor
dc.subject.cnpqCNPQ::CIENCIAS HUMANAS::EDUCACAO::PLANEJAMENTO E AVALIACAO EDUCACIONALpor
dc.titleUm modelo computacional de apoio à análise da opinião de alunos sobre práticas docentes por meio da mineração de dados educacionaispor
dc.typeTesepor
local.contributor.board1Silva, Leandro Augusto da
local.contributor.board1Latteshttp://lattes.cnpq.br/1396385111251741por
local.contributor.board2Omar, Nizam
local.contributor.board2Latteshttp://lattes.cnpq.br/2067336430076971por
local.contributor.board3Araújo Junior, Carlos Fernando de
local.contributor.board3Latteshttp://lattes.cnpq.br/9413606062591307por
local.contributor.board4Yamamoto, Cláudio Haruo
local.contributor.board4Latteshttp://lattes.cnpq.br/5376452909200749por
local.publisher.countryBrasilpor
local.publisher.departmentEscola de Engenharia Mackenzie (EE)por
local.publisher.initialsUPMpor
local.publisher.programEngenharia Elétricapor
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Engenharia Elétrica e Computação - Teses - EE Higienópolis