Ensino de Inteligência Artificial para Professores da Educação Básica: Uma Revisão Sistemática da Literatura
Resumo
A Inteligência Artificial (IA) tem impactado diversos setores da sociedade, promovendo mudanças significativas. No campo educacional, um dos principais desafios é a capacitação de professores da Educação Básica em IA. No entanto, há uma escassez de estudos que consolidem abordagens, metodologias e desafios das iniciativas de qualificação docente. Para enfrentar essa lacuna, foi conduzida uma Revisão Sistemática da Literatura, selecionando 38 estudos. Os resultados indicam que todas as iniciativas ocorrem fora da América Latina e que não há um referencial consolidado para a alfabetização em IA na formação docente. Assim, este estudo contribui como referência para pesquisas futuras sobre a integração da IA na Educação Básica brasileira.Referências
Abramowitz, B. and Antonenko, P. (2022). In-service teachers’ (mis)conceptions of artificial intelligence in k-12 science education. Journal of Research on Technology in Education, 55:1–15.
Ayanwale, M., Frimpong, E., Opesemowo, O., and Sanusi, I. (2024a). Exploring factors that support pre-service teachers’ engagement in learning artificial intelligence. Journal for STEM Education Research, pages 1–31.
Ayanwale, M. A., Adelana, O. P., Molefi, R. R., Adeeko, O., and Ishola, A. M. (2024b). Examining artificial intelligence literacy among pre-service teachers for future class-rooms. Computers and Education Open, 6:100179.
Carmichael, M. (2024). The Ipsos AI Monitor 2024. Technical report, IPSOS. Acessado em 10 de fevereiro de 2025.
Casal-Otero, L., Catala, A., Fernández-Morante, C., Taboada, M., Cebreiro, B., and Barro, S. (2023). Ai literacy in k-12: A systematic literature review. International Journal of STEM Education, 10:29.
Celik, I. (2022). Towards intelligent-tpack: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (ai)-based tools into education. Computers in Human Behavior, pages 1–12.
Cheng, E. C. K. and Wang, T. (2023). Leading digital transformation and eliminating barriers for teachers to incorporate artificial intelligence in basic education in hong kong. Computers and Education: Artificial Intelligence, 5:100171.
Chiu, T. K. and Chai, C.-s. (2020). Sustainable curriculum planning for artificial intelligence education: A self-determination theory perspective. Sustainability, 12(14).
Chiu, T. K. F., Meng, H., Chai, C.-S., King, I., Wong, S., and Yam, Y. (2022). Creation and evaluation of a pretertiary artificial intelligence (ai) curriculum. IEEE Transactions on Education, 65(1):30–39.
Cu, B. and Fujimoto, T. (2023). Design of an instructional framework to deepen teaching and learning experience in regular ai education for middle/high school levels. In Selvaraj, H., Chmaj, G., and Zydek, D., editors, Advances in Systems Engineering, pages 413–423, Cham. Springer Nature Switzerland.
DiPaola, D., Moore, K. S., Ali, S., Perret, B., Zhou, X., Zhang, H., and Lee, I. (2023). Make-a-thon for middle school ai educators. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1, SIGCSE 2023, page 305–311, New York, NY, USA. Association for Computing Machinery.
Du, H., Sun, Y., Jiang, H., Islam, A. Y. M. A., and Gu, X. (2024). Exploring the effects of ai literacy in teacher learning: an empirical study. Humanities and Social Sciences Communications, 11:1–10.
Eurostat (2025). Use of artificial intelligence in enterprises. Acessado em 10 de fevereiro de 2025.
Ferrara, E. (2024). Fairness and bias in artificial intelligence: A brief survey of sources, impacts, and mitigation strategies. Sci, 6(1).
Fundi, M., Sanusi, I. T., Oyelere, S. S., and Ayere, M. (2024). Advancing ai education: Assessing kenyan in-service teachers’ preparedness for integrating artificial intelligence in competence-based curriculum. Computers in Human Behavior Reports, 14:100412.
Hsu, T.-C., Hsu, T.-P., and Lin, Y.-T. (2023). The artificial intelligence learning anxiety and self-efficacy of in-service teachers taking ai training courses. In 2023 International Conference on Artificial Intelligence and Education (ICAIE), pages 97–101.
Hur, J. (2024). Fostering ai literacy: overcoming concerns and nurturing confidence among preservice teachers. Information and Learning Sciences, 126.
Jatileni, C., Sanusi, I., Olaleye, S., Ayanwale, M., Agbo, F., and Oyelere, P. (2023). Artificial intelligence in compulsory level of education: perspectives from namibian in-service teachers. Education and Information Technologies, 29.
Jayasuriya, S., Swisher, K., Rego, J. D., Chandran, S., Mativo, J., Kurz, T., Collins, C. E., Robinson, D. T., and Pidaparti, R. (2024). Imagesteam: teacher professional development for integrating visual computing into middle school lessons. In Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence and Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence and Fourteenth Symposium on Educational Advances in Artificial Intelligence, AAAI’24/IAAI’24/EAAI’24. AAAI Press.
Jetzinger, F., Baumer, S., and Michaeli, T. (2024). Artificial intelligence in compulsory k-12 computer science classrooms: A scalable professional development offer for computer science teachers. In Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1, SIGCSE 2024, page 590–596, New York, NY, USA. Association for Computing Machinery.
Kandlhofer, M., Weixelbraun, P., Menzinger, M., Steinbauer-Wagner, G., and Kemenesi, Á. (2023). Education and awareness for artificial intelligence. In Pellet, J.-P. and Parriaux, G., editors, Informatics in Schools. Beyond Bits and Bytes: Nurturing Informatics Intelligence in Education, pages 3–12, Cham. Springer Nature Switzerland.
Kim, K. and Kwon, K. (2023). Exploring the ai competencies of elementary school teachers in south korea. Computers and Education: Artificial Intelligence, 4:100137.
Kim, S.-W. (2024). Development of a tpack educational program to enhance pre-service teachers’ teaching expertise in artificial intelligence convergence education. International Journal on Advanced Science, Engineering and Information Technology, 14(1):1–9.
Kong, S.-C. and Yang, Y. (2024). A human-centered learning and teaching framework using generative artificial intelligence for self-regulated learning development through domain knowledge learning in k–12 settings. IEEE Transactions on Learning Technologies, 17:1562–1573.
Lee, I. and Moore, K. (2024). An effectiveness study of teacher-led ai literacy curriculum in k-12 classrooms. Proceedings of the AAAI Conference on Artificial Intelligence, 38:23318–23325.
Lin, P. and Van Brummelen, J. (2021). Engaging teachers to co-design integrated ai curriculum for k-12 classrooms. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, CHI ’21, New York, NY, USA. Association for Computing Machinery.
Lorenz, U. and Romeike, R. (2023). What is ai-pack? – outline of ai competencies for teaching with dpack. In Informatics in Schools. Beyond Bits and Bytes: Nurturing Informatics Intelligence in Education: 16th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives, ISSEP 2023, Lausanne, Switzerland, October 23–25, 2023, Proceedings, page 13–25, Berlin, Heidelberg. Springer-Verlag.
Ministério da Ciência, T. e. I. (2021). Estratégia brasileira de inteligência artificial - ebia. Acessado em 5 de fevereiro de 2025.
Ministério da Educação (MEC) (2022). Computação na Educação Básica - Complemento à BNCC. Acessado em 10 de fevereiro de 2025.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P., and Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372.
Polak, S., Schiavo, G., and Zancanaro, M. (2022). Teachers’ perspective on artificial intelligence education: an initial investigation. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems, CHI EA ’22, New York, NY, USA. Association for Computing Machinery.
Pu, S., Ahmad, N. A., Khambari, N., Yap, N., and Ahrari, S. (2021). Improvement of pre-service teachers’ practical knowledge and motivation about artificial intelligence through a service-learning-based module in guizhou, china: A quasi-experimental study. Asian Journal of University Education, 17:203–219.
Russell, S. and Norvig, P. (2010). Artificial Intelligence: A Modern Approach. Prentice Hall, Upper Saddle River, NJ, 3rd edition.
Salas-Pilco, S. Z., Xiao, K., and Hu, X. (2022). Artificial intelligence and learning analytics in teacher education: A systematic review. Education Sciences, 12(8).
Sanusi, I., Oyelere, S., and Omidiora, J. (2021). Exploring teachers’ preconceptions of teaching machine learning in high school: A preliminary insight from africa. Computers and Education Open, 3:100072.
Saura, J. R., Ribeiro-Soriano, D., and Palacios-Marqués, D. (2022). Assessing behavioral data science privacy issues in government artificial intelligence deployment. Government Information Quarterly, 39(4):101679.
Sperling, K., Stenberg, C.-J., McGrath, C., Åkerfeldt, A., Heintz, F., and Stenliden, L. (2024). In search of artificial intelligence (ai) literacy in teacher education: A scoping review. Computers and Education Open, 6:100169.
Sun, J., Ma, H., Zeng, Y., Han, D., and Jin, Y. (2022). Promoting the ai teaching competency of k-12 computer science teachers: A tpack-based professional development approach. Education and Information Technologies, 28:1–25.
Vazhayil, A., Shetty, R., Bhavani, R. R., and Akshay, N. (2019). Focusing on teacher education to introduce ai in schools: Perspectives and illustrative findings. In 2019 IEEE Tenth International Conference on Technology for Education (T4E), pages 71–77.
Velander, J., Ahmed Taiye, M., Otero, N., Milrad, M., and Zijlema, A. (2023a). Reflections on methods for eliciting teachers understanding, attitudes and emotions about ai. In Milrad, M., Otero, N., Sánchez-Gómez, M. C., Mena, J. J., Durães, D., Sciarrone, F., Alvarez-Gómez, C., Rodrigues, M., Vittorini, P., Gennari, R., Di Mascio, T., Temperini, M., and De la Prieta, F., editors, Methodologies and Intelligent Systems for Technology Enhanced Learning, 13th International Conference, pages 124–135, Cham. Springer Nature Switzerland.
Velander, J., Taiye, M., Otero, N., and Milrad, M. (2023b). Artificial intelligence in k-12 education: eliciting and reflecting on swedish teachers’ understanding of ai and its implications for teaching & learning. Education and Information Technologies, 29:1–21.
Wang, X., Li, L., Tan, S. C., Yang, L., and Lei, J. (2023). Preparing for ai-enhanced education: Conceptualizing and empirically examining teachers’ ai readiness. Computers in Human Behavior, 146:107798.
Wei, Q., Li, M., Xiang, K., and Qiu, X. (2020). Analysis and strategies of the professional development of information technology teachers under the vision of artificial intelligence. In 2020 15th International Conference on Computer Science & Education (ICCSE), pages 716–721.
Williams, R., Kaputsos, S., and Breazeal, C. (2021). Teacher perspectives on how to train your robot: A middle school ai and ethics curriculum. Proceedings of the AAAI Conference on Artificial Intelligence, 35:15678–15686.
Xie, S., Chen, X., Peng, S., and Zhang, S. (2023a). Pre-service teachers’ behavioral intention for ai-integrated instruction: A path analysis of the theory of motivation-opportunity-ability (moa). In 2023 5th International Conference on Computer Science and Technologies in Education (CSTE), pages 1–5.
Xie, Y., Lin, Q., Zheng, F., Yin, X., and Ouyang, Z. (2023b). The practice of “mooc plus theme lecture-artificial intelligence tutoring - proj ect practice (mooc+taip)” model to improve ai literacy of preschool teachers. In 2023 Twelfth International Conference of Educational Innovation through Technology (EITT), pages 106–112.
Younis, B. (2024). Effectiveness of a professional development program based on the instructional design framework for ai literacy in developing ai literacy skills among pre-service teachers. Journal of Digital Learning in Teacher Education, 40(3):142–158.
Yue, M., Jong, M., and Ng, D. T. K. (2024). Understanding k–12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education. Education and Information Technologies, 29:19505–19536.
Zarifhonarvar, A. (2024). Economics of ChatGPT: a labor market view on the occupational impact of artificial intelligence. Journal of Electronic Business & Digital Economics, 3(2):100–116.
Zhao, L., Wu, X., and Luo, H. (2022). Developing ai literacy for primary and middle school teachers in china: Based on a structural equation modeling analysis. Sustainability, 14(21).
Ayanwale, M., Frimpong, E., Opesemowo, O., and Sanusi, I. (2024a). Exploring factors that support pre-service teachers’ engagement in learning artificial intelligence. Journal for STEM Education Research, pages 1–31.
Ayanwale, M. A., Adelana, O. P., Molefi, R. R., Adeeko, O., and Ishola, A. M. (2024b). Examining artificial intelligence literacy among pre-service teachers for future class-rooms. Computers and Education Open, 6:100179.
Carmichael, M. (2024). The Ipsos AI Monitor 2024. Technical report, IPSOS. Acessado em 10 de fevereiro de 2025.
Casal-Otero, L., Catala, A., Fernández-Morante, C., Taboada, M., Cebreiro, B., and Barro, S. (2023). Ai literacy in k-12: A systematic literature review. International Journal of STEM Education, 10:29.
Celik, I. (2022). Towards intelligent-tpack: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (ai)-based tools into education. Computers in Human Behavior, pages 1–12.
Cheng, E. C. K. and Wang, T. (2023). Leading digital transformation and eliminating barriers for teachers to incorporate artificial intelligence in basic education in hong kong. Computers and Education: Artificial Intelligence, 5:100171.
Chiu, T. K. and Chai, C.-s. (2020). Sustainable curriculum planning for artificial intelligence education: A self-determination theory perspective. Sustainability, 12(14).
Chiu, T. K. F., Meng, H., Chai, C.-S., King, I., Wong, S., and Yam, Y. (2022). Creation and evaluation of a pretertiary artificial intelligence (ai) curriculum. IEEE Transactions on Education, 65(1):30–39.
Cu, B. and Fujimoto, T. (2023). Design of an instructional framework to deepen teaching and learning experience in regular ai education for middle/high school levels. In Selvaraj, H., Chmaj, G., and Zydek, D., editors, Advances in Systems Engineering, pages 413–423, Cham. Springer Nature Switzerland.
DiPaola, D., Moore, K. S., Ali, S., Perret, B., Zhou, X., Zhang, H., and Lee, I. (2023). Make-a-thon for middle school ai educators. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1, SIGCSE 2023, page 305–311, New York, NY, USA. Association for Computing Machinery.
Du, H., Sun, Y., Jiang, H., Islam, A. Y. M. A., and Gu, X. (2024). Exploring the effects of ai literacy in teacher learning: an empirical study. Humanities and Social Sciences Communications, 11:1–10.
Eurostat (2025). Use of artificial intelligence in enterprises. Acessado em 10 de fevereiro de 2025.
Ferrara, E. (2024). Fairness and bias in artificial intelligence: A brief survey of sources, impacts, and mitigation strategies. Sci, 6(1).
Fundi, M., Sanusi, I. T., Oyelere, S. S., and Ayere, M. (2024). Advancing ai education: Assessing kenyan in-service teachers’ preparedness for integrating artificial intelligence in competence-based curriculum. Computers in Human Behavior Reports, 14:100412.
Hsu, T.-C., Hsu, T.-P., and Lin, Y.-T. (2023). The artificial intelligence learning anxiety and self-efficacy of in-service teachers taking ai training courses. In 2023 International Conference on Artificial Intelligence and Education (ICAIE), pages 97–101.
Hur, J. (2024). Fostering ai literacy: overcoming concerns and nurturing confidence among preservice teachers. Information and Learning Sciences, 126.
Jatileni, C., Sanusi, I., Olaleye, S., Ayanwale, M., Agbo, F., and Oyelere, P. (2023). Artificial intelligence in compulsory level of education: perspectives from namibian in-service teachers. Education and Information Technologies, 29.
Jayasuriya, S., Swisher, K., Rego, J. D., Chandran, S., Mativo, J., Kurz, T., Collins, C. E., Robinson, D. T., and Pidaparti, R. (2024). Imagesteam: teacher professional development for integrating visual computing into middle school lessons. In Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence and Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence and Fourteenth Symposium on Educational Advances in Artificial Intelligence, AAAI’24/IAAI’24/EAAI’24. AAAI Press.
Jetzinger, F., Baumer, S., and Michaeli, T. (2024). Artificial intelligence in compulsory k-12 computer science classrooms: A scalable professional development offer for computer science teachers. In Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1, SIGCSE 2024, page 590–596, New York, NY, USA. Association for Computing Machinery.
Kandlhofer, M., Weixelbraun, P., Menzinger, M., Steinbauer-Wagner, G., and Kemenesi, Á. (2023). Education and awareness for artificial intelligence. In Pellet, J.-P. and Parriaux, G., editors, Informatics in Schools. Beyond Bits and Bytes: Nurturing Informatics Intelligence in Education, pages 3–12, Cham. Springer Nature Switzerland.
Kim, K. and Kwon, K. (2023). Exploring the ai competencies of elementary school teachers in south korea. Computers and Education: Artificial Intelligence, 4:100137.
Kim, S.-W. (2024). Development of a tpack educational program to enhance pre-service teachers’ teaching expertise in artificial intelligence convergence education. International Journal on Advanced Science, Engineering and Information Technology, 14(1):1–9.
Kong, S.-C. and Yang, Y. (2024). A human-centered learning and teaching framework using generative artificial intelligence for self-regulated learning development through domain knowledge learning in k–12 settings. IEEE Transactions on Learning Technologies, 17:1562–1573.
Lee, I. and Moore, K. (2024). An effectiveness study of teacher-led ai literacy curriculum in k-12 classrooms. Proceedings of the AAAI Conference on Artificial Intelligence, 38:23318–23325.
Lin, P. and Van Brummelen, J. (2021). Engaging teachers to co-design integrated ai curriculum for k-12 classrooms. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, CHI ’21, New York, NY, USA. Association for Computing Machinery.
Lorenz, U. and Romeike, R. (2023). What is ai-pack? – outline of ai competencies for teaching with dpack. In Informatics in Schools. Beyond Bits and Bytes: Nurturing Informatics Intelligence in Education: 16th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives, ISSEP 2023, Lausanne, Switzerland, October 23–25, 2023, Proceedings, page 13–25, Berlin, Heidelberg. Springer-Verlag.
Ministério da Ciência, T. e. I. (2021). Estratégia brasileira de inteligência artificial - ebia. Acessado em 5 de fevereiro de 2025.
Ministério da Educação (MEC) (2022). Computação na Educação Básica - Complemento à BNCC. Acessado em 10 de fevereiro de 2025.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P., and Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372.
Polak, S., Schiavo, G., and Zancanaro, M. (2022). Teachers’ perspective on artificial intelligence education: an initial investigation. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems, CHI EA ’22, New York, NY, USA. Association for Computing Machinery.
Pu, S., Ahmad, N. A., Khambari, N., Yap, N., and Ahrari, S. (2021). Improvement of pre-service teachers’ practical knowledge and motivation about artificial intelligence through a service-learning-based module in guizhou, china: A quasi-experimental study. Asian Journal of University Education, 17:203–219.
Russell, S. and Norvig, P. (2010). Artificial Intelligence: A Modern Approach. Prentice Hall, Upper Saddle River, NJ, 3rd edition.
Salas-Pilco, S. Z., Xiao, K., and Hu, X. (2022). Artificial intelligence and learning analytics in teacher education: A systematic review. Education Sciences, 12(8).
Sanusi, I., Oyelere, S., and Omidiora, J. (2021). Exploring teachers’ preconceptions of teaching machine learning in high school: A preliminary insight from africa. Computers and Education Open, 3:100072.
Saura, J. R., Ribeiro-Soriano, D., and Palacios-Marqués, D. (2022). Assessing behavioral data science privacy issues in government artificial intelligence deployment. Government Information Quarterly, 39(4):101679.
Sperling, K., Stenberg, C.-J., McGrath, C., Åkerfeldt, A., Heintz, F., and Stenliden, L. (2024). In search of artificial intelligence (ai) literacy in teacher education: A scoping review. Computers and Education Open, 6:100169.
Sun, J., Ma, H., Zeng, Y., Han, D., and Jin, Y. (2022). Promoting the ai teaching competency of k-12 computer science teachers: A tpack-based professional development approach. Education and Information Technologies, 28:1–25.
Vazhayil, A., Shetty, R., Bhavani, R. R., and Akshay, N. (2019). Focusing on teacher education to introduce ai in schools: Perspectives and illustrative findings. In 2019 IEEE Tenth International Conference on Technology for Education (T4E), pages 71–77.
Velander, J., Ahmed Taiye, M., Otero, N., Milrad, M., and Zijlema, A. (2023a). Reflections on methods for eliciting teachers understanding, attitudes and emotions about ai. In Milrad, M., Otero, N., Sánchez-Gómez, M. C., Mena, J. J., Durães, D., Sciarrone, F., Alvarez-Gómez, C., Rodrigues, M., Vittorini, P., Gennari, R., Di Mascio, T., Temperini, M., and De la Prieta, F., editors, Methodologies and Intelligent Systems for Technology Enhanced Learning, 13th International Conference, pages 124–135, Cham. Springer Nature Switzerland.
Velander, J., Taiye, M., Otero, N., and Milrad, M. (2023b). Artificial intelligence in k-12 education: eliciting and reflecting on swedish teachers’ understanding of ai and its implications for teaching & learning. Education and Information Technologies, 29:1–21.
Wang, X., Li, L., Tan, S. C., Yang, L., and Lei, J. (2023). Preparing for ai-enhanced education: Conceptualizing and empirically examining teachers’ ai readiness. Computers in Human Behavior, 146:107798.
Wei, Q., Li, M., Xiang, K., and Qiu, X. (2020). Analysis and strategies of the professional development of information technology teachers under the vision of artificial intelligence. In 2020 15th International Conference on Computer Science & Education (ICCSE), pages 716–721.
Williams, R., Kaputsos, S., and Breazeal, C. (2021). Teacher perspectives on how to train your robot: A middle school ai and ethics curriculum. Proceedings of the AAAI Conference on Artificial Intelligence, 35:15678–15686.
Xie, S., Chen, X., Peng, S., and Zhang, S. (2023a). Pre-service teachers’ behavioral intention for ai-integrated instruction: A path analysis of the theory of motivation-opportunity-ability (moa). In 2023 5th International Conference on Computer Science and Technologies in Education (CSTE), pages 1–5.
Xie, Y., Lin, Q., Zheng, F., Yin, X., and Ouyang, Z. (2023b). The practice of “mooc plus theme lecture-artificial intelligence tutoring - proj ect practice (mooc+taip)” model to improve ai literacy of preschool teachers. In 2023 Twelfth International Conference of Educational Innovation through Technology (EITT), pages 106–112.
Younis, B. (2024). Effectiveness of a professional development program based on the instructional design framework for ai literacy in developing ai literacy skills among pre-service teachers. Journal of Digital Learning in Teacher Education, 40(3):142–158.
Yue, M., Jong, M., and Ng, D. T. K. (2024). Understanding k–12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education. Education and Information Technologies, 29:19505–19536.
Zarifhonarvar, A. (2024). Economics of ChatGPT: a labor market view on the occupational impact of artificial intelligence. Journal of Electronic Business & Digital Economics, 3(2):100–116.
Zhao, L., Wu, X., and Luo, H. (2022). Developing ai literacy for primary and middle school teachers in china: Based on a structural equation modeling analysis. Sustainability, 14(21).
Publicado
20/07/2025
Como Citar
WALDER, Jorge E. C.; LIMA, Anderson C. de; C. JUNIOR, Amaury A. de; REIS, Valéria Quadros dos.
Ensino de Inteligência Artificial para Professores da Educação Básica: Uma Revisão Sistemática da Literatura. In: WORKSHOP SOBRE EDUCAÇÃO EM COMPUTAÇÃO (WEI), 33. , 2025, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 315-329.
ISSN 2595-6175.
DOI: https://doi.org/10.5753/wei.2025.8076.
