Um software baseado no perfil de estudantes para recomendação de objetos de aprendizagem

• Ano de defesa: 2017
• Autor(a) principal: Mendes, Tiago de Avila
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade de Passo Fundo; Instituto de Ciências Exatas e Geociências – ICEG; BR; UPF; Programa de Pós-Graduação em Computação Aplicada
• Palavras-chave em Português: Tecnologia apropriada; Programas de computador; Educação.; Appropriate technology; Computer programs; Education.; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://repositorio.upf.br/handle/123456789/1745

Technological evolution in the last decades has brought about important transformations that have directly impacted people's lives. Every day new solutions and opportunities for problem solving are presented to society. In this world of intense changes and constant technological developments, all areas are evolving in order to make life easier for people. Examples of these technologies are the recommendation systems and user profile modeling applied to education. In this context, the resources of communication, collaboration and interaction between students and teachers are important allies for the qualification of teaching and learning. Collaborative learning environments, computational tools for interaction and visualization, as well as educational content available anytime, anywhere, are resources that can improve the quality of teaching. Among these technologies, e-learning (electronic learning), b-learning (blended learning) and m-learning (mobile learning) are increasingly being used in learning environments. Given this context, this dissertation aims to present a software that uses students’ profiles as a base for recommending learning objects. The purpose is to assist the teacher in monitoring student learning and to give students a view of their development in relation to a discipline or content. This software employs user profile modeling techniques and a recommendation-based method.