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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

AnÃlise do contexto e dos resultados da aprendizagem da avaliaÃÃo educacional em um curso de graduaÃÃo em Engenharia / Analysis of the context and results of educational evaluation of learning in an undergraduate degree in Engineering

Francisco Herbert Lima Vasconcelos 20 March 2015 (has links)
Banco do Nordeste do Brasil / A avaliaÃÃo educacional dispÃe de mÃtodos para a obtenÃÃo de dados que podem ser Ãteis para avaliar grupos de indivÃduos (alunos, professores, administradores, tÃcnicos e outros), projetos, produtos e materiais, instituiÃÃes e sistemas educacionais, nos seus diversos nÃveis e competÃncias. No campo da educaÃÃo em engenharia, os processos avaliativos podem ajudar os gestores a tomarem decisÃes e a realizarem mudanÃas em cursos de graduaÃÃo. Esta tese investiga de forma inÃdita uma nova abordagem para a anÃlise e interpretaÃÃo de dados no campo da educaÃÃo em engenharia com Ãnfase no processo de avaliaÃÃo, levando em consideraÃÃo dois aspectos de modo integrado: a) a percepÃÃo/opiniÃo dos estudantes sobre o contexto/ambiente educacional (Learning Context - LC) e b) os resultados/rendimentos obtidos pelos mesmos discentes (Learning Outcomes - LO). Para a realizaÃÃo desta pesquisa, foram coletados dados de estudantes do curso de graduaÃÃo em Engenharia de TeleinformÃtica (ETI) do Centro de Tecnologia (CT) da Universidade Federal do Cearà (UFC). Os dados de LC foram coletados a partir da aplicaÃÃo do instrumento SEEQ (Studentâs Evaluation of Educational Quality) da metodologia SETE (Student Evaluate Teaching Effetivecness). Os dados de LO foram coletados a partir das informaÃÃes dos resultados de desempenho da aprendizagem dos mesmos discentes. Na realizaÃÃo do processamento da informaÃÃo dos dados matriciais e tensoriais obtidos, foram utilizadas duas ferramentas matemÃticas: a decomposiÃÃo bilinear, por meio da AnÃlise de Componentes Principais (Principal Component Analysis - PCA) e a decomposiÃÃo multilinear tensorial por meio da AnÃlise de Fatores Paralelos (Parallel Factor Analysis - PARAFAC). Os resultados obtidos permitem identificar caracterÃsticas comuns e semelhanÃas em componentes curriculares, tanto em termos da percepÃÃo quanto do desempenho dos estudantes. Os modelos PCA e PARAFAC tambÃm demonstraram um potencial significativo para extrair informaÃÃes de dados relacionados com variÃveis latentes em contextos educativos. / Educational evaluation provides methods to obtain data that can be useful for evaluating groups of individuals (students, teachers, administrators, technicians and others), projects, products and materials, educational institutions and systems at different levels and skills. In engineering education, evaluation processes can help managers to make decisions and changes in undergraduate courses. This thesis investigates in unprecedented way a new approach to the analysis and interpretation of data in the field of engineering education with emphasis in the evaluation process, taking into account two aspects in an integrated manner: a) perception / opinion of students about the context / educational environment (Learning Context - LC) and b) the results / income earned by the same students (Learning outcomes - LO). For this research, we collected data related to undergraduate students in Teleinformatics Engineering (TEI), at Technology Center (CT) of the Federal University of Cearà (UFC). LC data were collected from the application of SEEQ (Studentâs Evaluation of Educational Quality) instrument of SETE (Student Teaching Evaluate Effetivecness) methodology. The LO data was collected from the information of the performance of the studentsâ learning outcomes. Carrying out the information processing of the obtained tensor and matrix data, we have used two mathematical tools: the bilinear decomposition, called Principal Component Analysis - PCA decomposition and the multilinear tensor decomposition by Parallel Factor Analysis - PARAFAC. The results allow us to identify common features and similarities in curriculum components, both in terms of perception as the performance of students. The PCA and PARAFAC models also showed significant potential to extract data information related to latent variables in educational settings.

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