Tendências de Pesquisas em Mineração de Dados Educacionais em MOOCs: um Mapeamento Sistemático
DOI:
https://doi.org/10.5753/rbie.2020.28.0.491Keywords:
MOOCs, Mineração de Dados Educacionais, Mapeamento SistemáticoAbstract
Massive Open Online Courses (MOOCs) são uma modalidade de curso que utilizam plataformas online e atraem diferentes perfis de estudantes, ofertando oportunidades de qualificação - seja formal ou informal - em um formato bastante dinâmico. Uma característica das plataformas que ofertam tais cursos é a capacidade de armazenar uma grande quantidade de dados, o que possibilitou a exploração destes dados por meio de técnicas de Mineração de Dados Educacionais (MDE). Nesse contexto, foi conduzido um mapeamento sistemático de literatura em cinco bases de dados com o propósito de verificar quais as vertentes de estudos em destaque quanto ao uso de MDE em MOOCs. A busca compreendeu o período de 2015 a 2020, sendo que 158 foram selecionados. Os resultados revelaram que estudos relativos à Análise de Comportamento, Predição (de Desempenho, de Abandono, de Conclusão), Mineração de Texto e Sistemas de Recomendação são os mais frequentes. Além disso, foram identificadas áreas com potencial de exploração, como Social Network Analysis (SNA), Digital Learning Ecosystem (DLE) e Análise de Mind Wandering (MW). Ademais, foram levantados métodos e ferramentas usados nas pesquisas, bem como desafios do uso de MDE na pesquisa sobre MOOC. Conclui-se que a questão do desequilíbrio de classes, provocado pela baixa adesão aos cursos, é um dos maiores desafios.
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Copyright (c) 2020 Vanessa Faria De Souza, Gabriela Trindade Perry
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