On the integration between Computational Thinking and Artificial Intelligence: a Systematic Literature Review
Abstract
The Fourth Industrial Revolution has been causing profound changes in 21st century society. In order to respond to the new challenges, governments around the world are trying to reformulate curricula and recognize the importance of teaching the fundamentals of computing from the early grades. Inserted in these foundations, two themes have stood out: the development of Computational Thinking and the introduction of the principles of Artificial Intelligence. This study aims to investigate the aspects of integration between these two important phenomena, Computational Thinking and Artificial Intelligence, through a Systematic Literature Review.
Keywords:
Computational thinking, Artificial Intelligence
References
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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.
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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.
Published
2021-11-22
How to Cite
CARUSO, André Luis Macedo; CAVALHEIRO, Simone André da Costa.
On the integration between Computational Thinking and Artificial Intelligence: a Systematic Literature Review. In: BRAZILIAN SYMPOSIUM ON COMPUTERS IN EDUCATION (SBIE), 32. , 2021, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 1051-1062.
DOI: https://doi.org/10.5753/sbie.2021.218125.
