Estratégias para o Ensino de Machine Learning para Estudantes em Vulnerabilidade Social no Ensino Fundamental e Médio: Um Resumo
Resumo
Este artigo não possui um resumo.Referências
Branch, R. M. (2009). Instructional Design: The ADDIE Approach. Yin, R. K. (2017). Case Study Research and Applications: Design and Methods.
IBM (2025). What is Machine Learning? Disponível em: [link].
Pedró, F. et al (2019). Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development. UNESCO.
Martins, R. M. (2024). Estratégias para o Ensino de Machine Learning para Estudantes em Vulnerabilidade Social no Ensino Fundamental e Médio. Tese (Doutorado em Ciência da Computação) PPGCC/Universidade Federal de Santa Catarina.
Martins, R. M., & Gresse von Wangenheim, C. (2024). Teaching Computing to Middle and High School Students from a Low Socio-Economic Status Background: A Systematic Literature Review.
Parker, M. C., & Guzdial, M. (2015) A critical research synthesis of privilege in computing education. OECD PISA (2019).
Petersen, K. et al. (2015). Guidelines for conducting systematic mapping studies in software engineering: An update.
PISA 2018 Results (Vol. II): Where All Students Can Succeed: Country Note Brazil.
Saunders, M. N. K., et al. (2019). Research Methods for Business Students.
Wunderlich, A. et al. (2021). Machine Learning for Business Students: An Experiential Learning Approach.
Su, J., & Zhong, Y. (2022). Artificial Intelligence (AI) in early childhood education: Curriculum design and future directions.
IBM (2025). What is Machine Learning? Disponível em: [link].
Pedró, F. et al (2019). Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development. UNESCO.
Martins, R. M. (2024). Estratégias para o Ensino de Machine Learning para Estudantes em Vulnerabilidade Social no Ensino Fundamental e Médio. Tese (Doutorado em Ciência da Computação) PPGCC/Universidade Federal de Santa Catarina.
Martins, R. M., & Gresse von Wangenheim, C. (2024). Teaching Computing to Middle and High School Students from a Low Socio-Economic Status Background: A Systematic Literature Review.
Parker, M. C., & Guzdial, M. (2015) A critical research synthesis of privilege in computing education. OECD PISA (2019).
Petersen, K. et al. (2015). Guidelines for conducting systematic mapping studies in software engineering: An update.
PISA 2018 Results (Vol. II): Where All Students Can Succeed: Country Note Brazil.
Saunders, M. N. K., et al. (2019). Research Methods for Business Students.
Wunderlich, A. et al. (2021). Machine Learning for Business Students: An Experiential Learning Approach.
Su, J., & Zhong, Y. (2022). Artificial Intelligence (AI) in early childhood education: Curriculum design and future directions.
Publicado
20/07/2025
Como Citar
MARTINS, Ramon Mayor.
Estratégias para o Ensino de Machine Learning para Estudantes em Vulnerabilidade Social no Ensino Fundamental e Médio: Um Resumo. In: CONCURSO DE TESES E DISSERTAÇÕES (CTD), 38. , 2025, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 1-4.
ISSN 2763-8820.
DOI: https://doi.org/10.5753/ctd.2025.6931.
