Ensino de Machine Learning na Educação Básica: um Mapeamento Sistemático do Estado da Arte
Resumo
Uma vez que a Machine Learning (ML) está presente em vários aspectos de nossas vidas, novos desafios são apresentados à educação em ajudar estudantes a entender os potenciais e limites dessa tecnologia. Para obter um panorama do estado da arte do ensino de ML, foi realizado um mapeamento sistemático. Foram identificadas 39 unidades instrucionais focadas em conceitos básicos e redes neurais. Muitas unidades abordam apenas de forma parcial o processo de ML, como gerenciamento de dados, ou apresentam alguns processos apenas de forma abstrata. Os resultados obtidos indicam que o ensino de ML na educação básica pode aumentar o entendimento e interesse, bem como contextualizar conceitos de ML na vida dos estudantes.
Palavras-chave:
Machine Learning, Educação básica, Ensino
Referências
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Bordini, A. et al. (2017) “Pensamento Computacional nos Ensinos Fundamental e Médio: uma revisão sistemática”. In Anais do Simpósio Brasileiro de Informática na Educação, Recife, Brasil.
Evangelista, I. et al. (2018). Why are we not teaching machine learning at high school? A proposal. In: Proc. of the World Engineering Education Forum – Global Engineering Deans Council, Albuquerque, NM, USA.
Ferreira, M. N. F. et al. (2019) “Ensinando Design de Interface de Usuário na Educação Básica: Um Mapeamento Sistemático do Estado da Arte e Prática”. In Anais do Workshop de Informática na Escola, Brasília, Brasil.
Forbes. (2019) “AI goes to high school”. https://www.forbes.com/sites/insights-intelai/2019/05/22/ai-goes-to-high-school/#68826e3f1d0c
Google. (2016) “Trends in the State of Computer Science in U.S. K-12 Schools”. http://services.google.com/fh/files/misc/trends-in-the-state-of-computer-science-report.pdf
Grover, S., Pea, R. (2013) “Computational Thinking in K–12: A Review of the State of the Field”. Educational Researcher, 42(1), 38-43.
Haddaway, N. R. et al. (2015) “The role of Google Scholar in evidence reviews and its applicability to grey literature searching” PloS one, 10(9).
Heintz, F. et al. (2016) “A Review of Models for Introducing ComputationalThinking, Computer Science and Computing in K–12 Education”. In Proc. of IEEE Frontiers in Education Conference, Erie, PA, USA, 1-9.
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Hubwieser, P. et al. (2015) “A Global Snapshot of Computer Science Education in K-12 Schools”. In Proc. of the ITiCSE on Working Group Reports, Vilnius, Lithuania.
Kandlhofer, M. et al. (2016) “Artificial Intelligence and Computer Science in Education: From Kindergarten to University”. In Proc. of IEEE Frontiers in Education Conference, Erie, PA, USA.
Lye, S. Y., Koh, J. H. L. (2014) “Review on teaching and learning of computational thinking through programming: What is next for K-12?” Computers in Human Behavior, 41, 51-61.
Magno Jesus, A. et al. (2019) “Desenvolvimento do Pensamento Computacional por Meio da Colaboração: uma revisão sistemática da literatura”. Revista Brasileira de Informática na Educação, 27(2).
McGovern, A. et al. (2011) “Teaching Introductory Artificial Intelligence through Java- Based Games”. In Proc. of the 2nd Symposium on Educational Advances in Artificial Intelligence, San Francisco, CA, USA.
Petersen, K. et al. (2008) “Systematic mapping studies in software engineering”. In Proc. of the 12th International Conference on Evaluation and Assessment in Software Engineering, Bari, Italy, 68–77.
Royal Society. (2017) “Machine learning: the power and promise of computers that learn by example” https://royalsociety.org/~/media/policy/projects/machine-learning/publications/machine-learning-report.pdf
Tavares, L. A. et al. (2020) “Inteligência Artificial na Educação: Survey”. Brazilian Journal of Development, 6(7).
Torrey, L. (2012) “Teaching Problem-Solving in Algorithms and AI”. In Proc. of the 3rd Symposium on Educational Advances in Artificial Intelligence, Toronto, Canada.
Touretzky, D. S. et al. (2019a) “K-12 Guidelines for Artificial Intelligence: What Students Should Know”. In Proc. of the ISTE Conference, Philadelphia, PA, USA.
Touretzky, D. S. et al. (2019b) “Envisioning AI for K-12: What Should Every Child Know about AI?”. In Proc. of the 33 rd AAAI Conference on Artificial Intelligence, Honolulu, Hawaii, USA.
Touretzky, D. S., et al. (2019c) “K-12 AI Playground”. In Proc. of the CSTA Annual Conference, Philadelphia, PA, USA.
Wollowski, M. et al. (2016) “A Survey of Current Practice and Teaching of AI”. Proc. of the 30th AAAI Conference on Artificial Intelligence, Phoenix, AZ, USA.
Bordini, A. et al. (2017) “Pensamento Computacional nos Ensinos Fundamental e Médio: uma revisão sistemática”. In Anais do Simpósio Brasileiro de Informática na Educação, Recife, Brasil.
Evangelista, I. et al. (2018). Why are we not teaching machine learning at high school? A proposal. In: Proc. of the World Engineering Education Forum – Global Engineering Deans Council, Albuquerque, NM, USA.
Ferreira, M. N. F. et al. (2019) “Ensinando Design de Interface de Usuário na Educação Básica: Um Mapeamento Sistemático do Estado da Arte e Prática”. In Anais do Workshop de Informática na Escola, Brasília, Brasil.
Forbes. (2019) “AI goes to high school”. https://www.forbes.com/sites/insights-intelai/2019/05/22/ai-goes-to-high-school/#68826e3f1d0c
Google. (2016) “Trends in the State of Computer Science in U.S. K-12 Schools”. http://services.google.com/fh/files/misc/trends-in-the-state-of-computer-science-report.pdf
Grover, S., Pea, R. (2013) “Computational Thinking in K–12: A Review of the State of the Field”. Educational Researcher, 42(1), 38-43.
Haddaway, N. R. et al. (2015) “The role of Google Scholar in evidence reviews and its applicability to grey literature searching” PloS one, 10(9).
Heintz, F. et al. (2016) “A Review of Models for Introducing ComputationalThinking, Computer Science and Computing in K–12 Education”. In Proc. of IEEE Frontiers in Education Conference, Erie, PA, USA, 1-9.
Hiner, J. (2017) “AI will eliminate 1.8M jobs but create 2.3M by 2020, claims Gartner”. https://www.techrepublic.com/article/ai-will-eliminate-1-8m-jobs-but-create-2-3m-by-2020-claims-gartner
Hubwieser, P. et al. (2015) “A Global Snapshot of Computer Science Education in K-12 Schools”. In Proc. of the ITiCSE on Working Group Reports, Vilnius, Lithuania.
Kandlhofer, M. et al. (2016) “Artificial Intelligence and Computer Science in Education: From Kindergarten to University”. In Proc. of IEEE Frontiers in Education Conference, Erie, PA, USA.
Lye, S. Y., Koh, J. H. L. (2014) “Review on teaching and learning of computational thinking through programming: What is next for K-12?” Computers in Human Behavior, 41, 51-61.
Magno Jesus, A. et al. (2019) “Desenvolvimento do Pensamento Computacional por Meio da Colaboração: uma revisão sistemática da literatura”. Revista Brasileira de Informática na Educação, 27(2).
McGovern, A. et al. (2011) “Teaching Introductory Artificial Intelligence through Java- Based Games”. In Proc. of the 2nd Symposium on Educational Advances in Artificial Intelligence, San Francisco, CA, USA.
Petersen, K. et al. (2008) “Systematic mapping studies in software engineering”. In Proc. of the 12th International Conference on Evaluation and Assessment in Software Engineering, Bari, Italy, 68–77.
Royal Society. (2017) “Machine learning: the power and promise of computers that learn by example” https://royalsociety.org/~/media/policy/projects/machine-learning/publications/machine-learning-report.pdf
Tavares, L. A. et al. (2020) “Inteligência Artificial na Educação: Survey”. Brazilian Journal of Development, 6(7).
Torrey, L. (2012) “Teaching Problem-Solving in Algorithms and AI”. In Proc. of the 3rd Symposium on Educational Advances in Artificial Intelligence, Toronto, Canada.
Touretzky, D. S. et al. (2019a) “K-12 Guidelines for Artificial Intelligence: What Students Should Know”. In Proc. of the ISTE Conference, Philadelphia, PA, USA.
Touretzky, D. S. et al. (2019b) “Envisioning AI for K-12: What Should Every Child Know about AI?”. In Proc. of the 33 rd AAAI Conference on Artificial Intelligence, Honolulu, Hawaii, USA.
Touretzky, D. S., et al. (2019c) “K-12 AI Playground”. In Proc. of the CSTA Annual Conference, Philadelphia, PA, USA.
Wollowski, M. et al. (2016) “A Survey of Current Practice and Teaching of AI”. Proc. of the 30th AAAI Conference on Artificial Intelligence, Phoenix, AZ, USA.
Publicado
24/11/2020
Como Citar
MARQUES, Lívia Silva; VON WANGENHEIM, Christiane Gresse; ROSSA HAUCK, Jean Carlo.
Ensino de Machine Learning na Educação Básica: um Mapeamento Sistemático do Estado da Arte. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 31. , 2020, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 21-30.
DOI: https://doi.org/10.5753/cbie.sbie.2020.21.
