Integração entre Pensamento Computacional e Inteligência Artificial: uma Revisão Sistemática de Literatura
Resumo
A Quarta Revolução Industrial vem provocando profundas mudanças na sociedade do Século XXI. A fim de dar uma resposta aos desafios que se apresentam, os governos mundiais tentam reformular currículos e reconhecem a importância do ensino do dos fundamentos da Computação desde as séries iniciais. Inserido nesses fundamentos, dois temas tem se destacado: o desenvolvimento do Pensamento Computacional e a introdução dos princípios da Inteligência Artificial. Este estudo tem como objetivo investigar quais são os aspectos de integração entre esses dois importantes fenômenos, Pensamento Computacional e Inteligência Artificial, por meio de uma Revisão Sistemática de Literatura.
Palavras-chave:
Pensamento Computacioal, Inteligência Artificial
Referências
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Bobsin, R., Nunes, N., Kologeski, A., e Bona, A. (2020). O pensamento computacional presente na resolução de problemas investigativos de matemática na escola básica. In Anais do XXXI Simpósio Brasileiro de Informática na Educação, pages 1473–1482, Porto Alegre, RS, Brasil. SBC.
Brennan, K. e Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Studies in Computational Intelligence.
Camada, M. e Durães, G. (2020). Ensino da inteligência artificial na educação básica: um novo horizonte para as pesquisas brasileiras. In Anais do XXXI Simpósio Brasileiro de Informática na Educação, pages 1553–1562, Porto Alegre, RS, Brasil. SBC.
Chen, L., Babar, M. A., e Zhang, H. (2010). Towards an evidence-based understanding of electronic data sources. In EASE’10: Proceedings of the 14th international conference on Evaluation and Assessment in Software Engineering. BCS Learning and Development Ltd.
Chiazzese, G., Arrigo, M., Chifari, A., Lonati, V., e Tosto, C. (2019). Educational robotics in primary school: Measuring the development of computational thinking skills with the bebras tasks. Informatics, 6(4).
CSTA e ISTE (2011). Operational definition of computational thinking. Report, page 1.
Druga, S. (2018). GROWING UP WITH AI Cognimates: from coding to teaching machines. MIT Sloan School of Management, pages 1–113.
Estevez, J., Garate, G., e Grana, M. (2019). Gentle Introduction to Artificial Intelligence for High-School Students Using Scratch. IEEE Access, 7:179027–179036.
Gadanidis, G. (2017). Artificial intelligence, computational thinking, and mathematics education. International Journal of Information and Learning Technology, 34(2):133– 139.
Guarda, G. e Pinto, S. (2020). Dimensões do pensamento computacional: conceitos, práticas e novas perspectivas. In Anais do XXXI Simpósio Brasileiro de Informática na Educação, pages 1463–1472, Porto Alegre, RS, Brasil. SBC.
Haenlein, M. e Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Review, 61(4):5– 14. ISBN: 0008125619.
JAQUES, P. A., SIQUEIRA, S., BITTENCOURT, I., e PIMENTEL, M. (2020). Mapeamento sistemático e revisão sistemática da literatura em informática na educação. In Metodologia de Pesquisa Científica em Informática na Educação: Abordagem Quan- titativa (Volume 2). MPCEIE.
Kalelioglu, F., Gulbahar, Y., e Kukul, V. (2016). A framework for computational thinking based on a systematic research review. Baltic Journal of Modern Computing, 4:583– 596.
Kolb, D. A. (1984). Experiential learning : experience as the source of learning and development. Prentice-Hall, Englewood Cliffs, N.J.
Lin, Y. S., Chen, S. Y., Tsai, C. W., e Lai, Y. H. (2021). Exploring Computational Thinking Skills Training Through Augmented Reality and AIoT Learning. Frontiers in Psychology, 12(February):1–9.
Luca, G. D. e Chen, Y. (2021). Explainable Arti fi cial Intelligence for Work fl ow Verification in Visual IoT / Robotics Programming Language Environment. Journal of Artificial Intelligence and Technology, 1(1), 21–27., pages 21–27.
Mccarthy, J. (2004). What is Artificial Intelligence? Researchgate, pages 1–14.
Moreno-Leon, J., Roman-Gonzalez, M., e Robles, G. (2018). On computational thinking as a universal skill: A review of the latest research on this ability. IEEE Global Engineering Education Conference, EDUCON, 2018-April:1684–1689.
Morris, K. C., Schlenoff, C., e Srinivasan, V. (2017). Guest Editorial A Remarkable Resurgence of Artificial Intelligence and Its Impact on Automation and Autonomy. IEEE Transactions on Automation Science and Engineering, 14(2):407–409.
Mustafaraj, E., Umarova, K., Ibrbak, F., e Lee, S. (2018). Task-specific language modeling for selecting peer-written explanations. Proceedings of the 31st International Florida Artificial Intelligence Research Society Conference, FLAIRS 2018, pages 433– 438.
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Rodríguez-García, J. D., Moreno-León, J., Román-González, M., e Robles, G. (2020). LearningML: A tool to foster computational thinking skills through practical artificial intelligence projects. Revista de Educacion a Distancia, 20(63).
Schwab, K. (2016). The Fourth Industrial Revolution. World Economic Forum, Geneva.
Shih, W. C. (2019). Integrating computational thinking into the process of learning artificial intelligence. ACM International Conference Proceeding Series, pages 364–368.
Silapachote, P. e Srisuphab (2017). Teaching and Learning Computational Thinking through Solving Problems in Artificial Intelligence. IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), pages 50–54.
Van Brummelen, J., Shen, J. H., e Patton, E. W. (2019). The popstar, the poet, and the grinch: Relating artificial intelligence to the computational thinking framework with block-based coding. Proceedings of International Conference on Computational Thinking Education, pages 160–161.
Vico, F., Molina, M., Orden, D., Ortiz, J., García, R., e Masa, J. (2019). a Coding Curriculum for K-12 Education: the Evidence-Based Approach. EDULEARN19 Proceedings, 1(September):7102–7106.
Williams, R., Park, H. W., Oh, L., e Breazeal, C. (2019). Popbots: Designing an artificial intelligence curriculum for early childhood education. 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelli- gence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, pages 9729–9736.
Wing, J. M. (2006). Explanation-based learning. Computer Science Handbook, Second Edition.
Wing, J. M. (2011). Computational thinking—What and why? The Link Magazine.
Wong, G. K., Ma, X., Dillenbourg, P., e Huen, J. (2020). Broadening artificial intelligence education in K-12: Where to start? ACM Inroads, 11(1):20–29.
Yu, Y. e Chen, Y. (2018). Design and Development of High School Artificial Intelligence Textbook Based on Computational Thinking. OALib, 05(09):1–15.
Zeng, D. (2013). From computational thinking to ai thinking. IEEE Intelligent Systems, 28(6):2–4.
Bobsin, R., Nunes, N., Kologeski, A., e Bona, A. (2020). O pensamento computacional presente na resolução de problemas investigativos de matemática na escola básica. In Anais do XXXI Simpósio Brasileiro de Informática na Educação, pages 1473–1482, Porto Alegre, RS, Brasil. SBC.
Bobsin, R., Nunes, N., Kologeski, A., e Bona, A. (2020). O pensamento computacional presente na resolução de problemas investigativos de matemática na escola básica. In Anais do XXXI Simpósio Brasileiro de Informática na Educação, pages 1473–1482, Porto Alegre, RS, Brasil. SBC.
Brennan, K. e Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Studies in Computational Intelligence.
Camada, M. e Durães, G. (2020). Ensino da inteligência artificial na educação básica: um novo horizonte para as pesquisas brasileiras. In Anais do XXXI Simpósio Brasileiro de Informática na Educação, pages 1553–1562, Porto Alegre, RS, Brasil. SBC.
Chen, L., Babar, M. A., e Zhang, H. (2010). Towards an evidence-based understanding of electronic data sources. In EASE’10: Proceedings of the 14th international conference on Evaluation and Assessment in Software Engineering. BCS Learning and Development Ltd.
Chiazzese, G., Arrigo, M., Chifari, A., Lonati, V., e Tosto, C. (2019). Educational robotics in primary school: Measuring the development of computational thinking skills with the bebras tasks. Informatics, 6(4).
CSTA e ISTE (2011). Operational definition of computational thinking. Report, page 1.
Druga, S. (2018). GROWING UP WITH AI Cognimates: from coding to teaching machines. MIT Sloan School of Management, pages 1–113.
Estevez, J., Garate, G., e Grana, M. (2019). Gentle Introduction to Artificial Intelligence for High-School Students Using Scratch. IEEE Access, 7:179027–179036.
Gadanidis, G. (2017). Artificial intelligence, computational thinking, and mathematics education. International Journal of Information and Learning Technology, 34(2):133– 139.
Guarda, G. e Pinto, S. (2020). Dimensões do pensamento computacional: conceitos, práticas e novas perspectivas. In Anais do XXXI Simpósio Brasileiro de Informática na Educação, pages 1463–1472, Porto Alegre, RS, Brasil. SBC.
Haenlein, M. e Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Review, 61(4):5– 14. ISBN: 0008125619.
JAQUES, P. A., SIQUEIRA, S., BITTENCOURT, I., e PIMENTEL, M. (2020). Mapeamento sistemático e revisão sistemática da literatura em informática na educação. In Metodologia de Pesquisa Científica em Informática na Educação: Abordagem Quan- titativa (Volume 2). MPCEIE.
Kalelioglu, F., Gulbahar, Y., e Kukul, V. (2016). A framework for computational thinking based on a systematic research review. Baltic Journal of Modern Computing, 4:583– 596.
Kolb, D. A. (1984). Experiential learning : experience as the source of learning and development. Prentice-Hall, Englewood Cliffs, N.J.
Lin, Y. S., Chen, S. Y., Tsai, C. W., e Lai, Y. H. (2021). Exploring Computational Thinking Skills Training Through Augmented Reality and AIoT Learning. Frontiers in Psychology, 12(February):1–9.
Luca, G. D. e Chen, Y. (2021). Explainable Arti fi cial Intelligence for Work fl ow Verification in Visual IoT / Robotics Programming Language Environment. Journal of Artificial Intelligence and Technology, 1(1), 21–27., pages 21–27.
Mccarthy, J. (2004). What is Artificial Intelligence? Researchgate, pages 1–14.
Moreno-Leon, J., Roman-Gonzalez, M., e Robles, G. (2018). On computational thinking as a universal skill: A review of the latest research on this ability. IEEE Global Engineering Education Conference, EDUCON, 2018-April:1684–1689.
Morris, K. C., Schlenoff, C., e Srinivasan, V. (2017). Guest Editorial A Remarkable Resurgence of Artificial Intelligence and Its Impact on Automation and Autonomy. IEEE Transactions on Automation Science and Engineering, 14(2):407–409.
Mustafaraj, E., Umarova, K., Ibrbak, F., e Lee, S. (2018). Task-specific language modeling for selecting peer-written explanations. Proceedings of the 31st International Florida Artificial Intelligence Research Society Conference, FLAIRS 2018, pages 433– 438.
Raschka, S. e Mirjalili, V. (2019). Python Machine Learning - Third Edition. Expert Insight.
Rodríguez-García, J. D., Moreno-León, J., Román-González, M., e Robles, G. (2020). LearningML: A tool to foster computational thinking skills through practical artificial intelligence projects. Revista de Educacion a Distancia, 20(63).
Schwab, K. (2016). The Fourth Industrial Revolution. World Economic Forum, Geneva.
Shih, W. C. (2019). Integrating computational thinking into the process of learning artificial intelligence. ACM International Conference Proceeding Series, pages 364–368.
Silapachote, P. e Srisuphab (2017). Teaching and Learning Computational Thinking through Solving Problems in Artificial Intelligence. IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), pages 50–54.
Van Brummelen, J., Shen, J. H., e Patton, E. W. (2019). The popstar, the poet, and the grinch: Relating artificial intelligence to the computational thinking framework with block-based coding. Proceedings of International Conference on Computational Thinking Education, pages 160–161.
Vico, F., Molina, M., Orden, D., Ortiz, J., García, R., e Masa, J. (2019). a Coding Curriculum for K-12 Education: the Evidence-Based Approach. EDULEARN19 Proceedings, 1(September):7102–7106.
Williams, R., Park, H. W., Oh, L., e Breazeal, C. (2019). Popbots: Designing an artificial intelligence curriculum for early childhood education. 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelli- gence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, pages 9729–9736.
Wing, J. M. (2006). Explanation-based learning. Computer Science Handbook, Second Edition.
Wing, J. M. (2011). Computational thinking—What and why? The Link Magazine.
Wong, G. K., Ma, X., Dillenbourg, P., e Huen, J. (2020). Broadening artificial intelligence education in K-12: Where to start? ACM Inroads, 11(1):20–29.
Yu, Y. e Chen, Y. (2018). Design and Development of High School Artificial Intelligence Textbook Based on Computational Thinking. OALib, 05(09):1–15.
Zeng, D. (2013). From computational thinking to ai thinking. IEEE Intelligent Systems, 28(6):2–4.
Bobsin, R., Nunes, N., Kologeski, A., e Bona, A. (2020). O pensamento computacional presente na resolução de problemas investigativos de matemática na escola básica. In Anais do XXXI Simpósio Brasileiro de Informática na Educação, pages 1473–1482, Porto Alegre, RS, Brasil. SBC.
Publicado
22/11/2021
Como Citar
CARUSO, André Luis Macedo; CAVALHEIRO, Simone André da Costa.
Integração entre Pensamento Computacional e Inteligência Artificial: uma Revisão Sistemática de Literatura. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 32. , 2021, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 1051-1062.
DOI: https://doi.org/10.5753/sbie.2021.218125.
