Proposta de Melhoria dos Dados de Relatórios de uma Plataforma de MOOCS Brasileira

• Autor(a) principal: Souza, Vanessa Faria de
• Data de Publicação: 2020
• Outros Autores: Perry, Gabriela Trindade
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Revista Brasileira de Aprendizagem Aberta e a Distância
• Texto Completo: https://seer.abed.net.br/RBAAD/article/view/424
• topic: educational data mining, educational data analysis, virtual learning environments, massive and open online courses.; mineração de dados educacionais, análise de dados educacionais, ambientes virtuais de aprendizagem, cursos online massivos e abertos.

Most Virtual Learning Environments (VLEs) are not designed to make navigation records focused on data mining, but rather to inform teachers and students about pedagogical goals. However, the understanding that the information that can be extracted from the navigation records can be very relevant is gaining relevance, which motivates the vigorous interest in the area of educational data mining. In this sense, this article analyzes how data collected on the Moodle-based Lúmina platform, AVA, which provides Massive Open Online Courses (MOOCs) from the Federal University of Rio Grande do Sul (UFRGS), can be improved, allowing more information about students being extracted. As a model for this analysis, we used the Pittsburgh Science of Learning Center (PSLC) DataShop repository, which was originally designed to provide online educational resources and has been successful in applying the mining process. The goal is to propose adjustments to the UFRGS platform.