Uso dos algoritmos Machine Learning para analisar o Moodle e os telefones inteligentes no processo educativo da Física
DOI:
https://doi.org/10.1590/1983-3652.2023.41293Palavras-chave:
Moodle, Smartphones, Aprendizado de máquina, Aprendizagem profunda, EducaçãoResumo
O objetivo deste estudo misto é analisar as percepções dos alunos sobre o uso do Moodle e smartphones no processo educacional de Física por meio da Ciência de Dados. Os algoritmos de Machine Learning utilizados são regressão linear, árvore de decisão e deep learning. Neste estudo, a incorporação do Moodle facilitou a entrega de tarefas, a consulta dos conteúdos, a comunicação e a revisão dos recursos multimédia. Os smartphones permitiram ainda o acesso a plataformas virtuais de aprendizagem, a utilização de aplicações móveis e a comunicação a partir de qualquer lugar. Os resultados dos algoritmos de regressão linear e deep learning indicam que o uso do Moodle e smartphones influencia positivamente a motivação dos alunos, a assimilação do conhecimento e a satisfação no curso de Física. Por outro lado, o algoritmo da árvore de decisão determina seis modelos preditivos. As limitações são as técnicas de Machine Learning utilizadas e a análise de ferramentas tecnológicas para a assimilação do conhecimento, motivação e satisfação. Estudos futuros podem analisar o uso do Moodle e smartphones para papel ativo e desenvolvimento de habilidades em várias escolas de ensino médio e universidades. Da mesma forma, algoritmos de Machine Learning sobre florestas aleatórias e regressão logística podem ser usados para analisar o impacto dessas ferramentas tecnológicas no desempenho acadêmico. Por último, a incorporação do Moodle e dos smartphones permite a atualização dos cursos e o desenho de atividades criativas a distância.
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Copyright (c) 2023 Ricardo-Adán Salas-Rueda , Jesús Ramírez-Ortega, Selene-Marisol Martínez-Ramírez, Clara Alvarado-Zamorano
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