Meta-Mooc: Uma Ferramenta para geração de Moocs Adaptativos e Personalizáveis

• Ano de defesa: 2017
• Autor(a) principal: Dias Júnior, José Barbosa
• 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: Engenharia Elétrica; MOOCs (Instrução baseada na Web); Ensino a Distância; Ensino auxiliado por computador; Tecnologia Educacional; MOOC; Sistemas Adaptativos; Meta-MOOC; Interface Adaptativa; Adaptação de Contexto; Adaptative Systems; Adaptative Interface; Context Adptaware; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: https://repositorio.ufu.br/handle/123456789/21135; http://dx.doi.org/10.14393/ufu.te.2018.756

The emergence of Massive Open Online Courses (MOOCs) has revolutionized educational methods. Due to the rapid expansion of their use, MOOCs now represent one of the main resources for universal access to education, enabling the democratization of knowledge in formal or informal contexts for students who are geographically dispersed, without any prerequisites. However, these courses face challenges and questions concerning high dropout rates, pedagogical effectiveness, and doubts about what and how to study. The present work presents the evaluation of a meta-MOOC model to use context-sensitive techniques together with learning styles for the automatic creation of adaptive and personalizable MOOCs. The contribution of this work is a generic model for automated generation of Adaptive and Customizable MOOCs, to address the limitations and problems typical of MOOCs, which considers the identification of learning styles and preferences of the students of these courses. And the presentation of an open tool, based on the proposed model, validated with the generation of two Adaptive MOOCs: one of Augmented Reality and another, of Cellular Biology, generated by the tool as final result.