HíbriDoC: Método para a Classificação de Atividades de Computação Desplugada para uso no Ensino Híbrido

• Ano de defesa: 2023
• Autor(a) principal: QUESIA DE ARAUJO SANTOS
• Orientador(a): Anderson Correa de Lima
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Fundação Universidade Federal de Mato Grosso do Sul
• País: Brasil
• Palavras-chave em Português: Computação Desplugada, Ensino Híbrido, Ensino Remoto, Atividades, Classificador
• Link de acesso: https://repositorio.ufms.br/handle/123456789/6512

Computer Science Unplugged is a technique that consists of teaching computer science concepts and problems through a collection of face-to-face activities without the use of a computer (commonly referred to as "unplugged" activities). These activities have attracted the interest of teachers and researchers and have been used in various countries around the world, from primary to higher education. However, as in other fields, the recent Covid-19 pandemic has affected engagement in learning activities, due to changes in student-teacher interaction and the adoption of remote teaching methods. This new context has created challenges for the use of Computer Science Unplugged, including its integration into remote teaching and Blended Learning. Addressing this challenge, this work proposes a method for classifying Unplugged Computing Activities, with the aim of identifying which activities are most suitable for remote and Blended Learning. The results of our studies show that the tool is suitable for classifying activities. In particular, the study contributes to the field of computer science education by providing a tool capable of classifying Unplugged Computing Activities for use in Blended Learning.