Desenvolvimento de um sistema de recomendação baseado na teoria das inteligências múltiplas para o ensino de lógica de programação

• Ano de defesa: 2019
• Autor(a) principal: Correa, Deborah Godoy Martins [UNIFESP]
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• dARK ID: ark:/48912/001300002bdvj
• Idioma: por
• Instituição de defesa: Universidade Federal de São Paulo (UNIFESP)
• Palavras-chave em Português: Learning; Learning Styles; Multiple Intelligence; Programming Logic; Teaching; Aprendizagem; Ensino; Estilos De Aprendizagem; Inteligências Múltiplas; Lógica De Programação
• Link de acesso: https://sucupira.capes.gov.br/sucupira/public/consultas/coleta/trabalhoConclusao/viewTrabalhoConclusao.jsf?popup=true&id_trabalho=7950995; https://repositorio.unifesp.br/handle/11600/59183

Teaching and learning programming logic continues to be an obstacle in the academic field. Considered one of the most important curricular units in the field of sciences and technologies, it remains the focus of much investigation in the attempt to minimize its high failure rates. Many methodologies and tools have been proposed, but with occasional and timely positive results. This paper highlights the main difficulties encountered in the context of the teaching and learning processes of Programming Logic and proposes a didactic-methodological tool that uses Armstrong's multiple intelligences inventory and the Honey-Alonso learning style questionnaire. The system provides a set of recommendations that allow students to improve their self-knowledge, and give teachers subsidies that can favor the teaching and learning processes and train technically, personally and professionally qualified citizens. The data analysis allows rethinking the ways of transmitting knowledge and subsidizing actions that effectively develop skills and abilities, which can contribute to decrease evasion and increase the approval rate in the discipline of Programming Logic.