Repositório personalizado ao candidato para concursos públicos: aplicando métodos efetivos para construção do conhecimento

• Ano de defesa: 2021
• Autor(a) principal: Silva, Mislene Dalila da
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Engenharia Elétrica
• Palavras-chave em Português: Aprendizagem; Learning; Aprendizagem efetiva; Effective learning; Mapa de Conhecimento Estruturado; Structured Knowledge Map; Método de Memorização Exponencial Efetivo na Base Binária; Exponential Memorization Method Effective on Binary Base; Tabela de Avaliação Qualitativa; Qualitative Evaluation Table; CNPQ::CIENCIAS EXATAS E DA TERRA; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA; CNPQ::CIENCIAS HUMANAS::EDUCACAO; Engenharia elétrica; Educação afetiva; Memorização - Métodos de ensino
• Link de acesso: https://repositorio.ufu.br/handle/123456789/33508; http://doi.org/10.14393/ufu.te.2021.584

The thesis was the development of a customized repository for the candidate for public tenders. Therefore, the general objective was to develop a personalized and adaptive environment for students in preparatory courses for public exams, so that they learn according to the level of ability they have, consolidating knowledge in memorization intervals through the Effective Exponential Memorization Method in Binary Base (MMEEBB). In order to maximize student learning capacity and mitigate hidden variables in relation to their development. The content made available to the student will be classified by a specialist professor in the discipline, in order to indicate the best study material. The student can manage their study schedule according to the contest data concurrently with the MMEEBB to follow the reinforcement of the learning interval. Thus, the work is structured in bibliographic, field, exploratory and descriptive research, in which information regarding recommendation systems, competitions, assessments, learning and Structured Knowledge Map (MCE) and MMEEBB methods are collected.