Uso de Agentes Conversacionais com IAGen na Personalização do Aprendizado na Educação Básica: uma Revisão Sistemática da Literatura
Resumo
A personalização do ensino na Educação Básica enfrenta desafios de escalabilidade frente à heterogeneidade discente. Agentes conversacionais baseados em Inteligência Artificial Generativa (IAGen) surgem como alternativa para viabilizar trilhas adaptativas e inclusivas. Esta Revisão Sistemática da Literatura (RSL), orientada pela estratégia PICOC, mapeou estudos primários (2019-2025) nas bases de Computação e Educação para analisar esse cenário. Os resultados constatam a hegemonia técnica da família GPT, aplicada majoritariamente na adaptação dinâmica de materiais didáticos e no feedback formativo automatizado. Contudo, evidenciam-se lacunas como a incipiência de arquiteturas híbridas e a escassa exploração de mecanismos de Retrieval-Augmented Generation (RAG). Conclui-se que o mapeamento dessas tendências e hiatos oferece diretrizes essenciais para o desenvolvimento de soluções que promovam equidade e personalização em larga escala.
Palavras-chave:
Agentes Conversacionais, Inteligência Artificial Generativa, Personalização do Aprendizado
Referências
Abdel-Hafez, A. and Yousef, A. (2025). A dataset of media articles on chatgpt. In Proceeding - 12th International Conference on Information Technology: Innovation Technologies, ICIT 2025, pages 465–470. Institute of Electrical and Electronics Engineers Inc.
Abdullahi, M. E., Abdulsalam, M. O., and Ekele, O. A. (2025). The impact of generative ai in personalized learning on students learning outcomes; teachers perception of impact of ai in the 21st century. Babcock University Journal of Education, 10.
Almufarreh, A. (2024). Determinants of students' satisfaction with ai tools in education: A pls-sem-ann approach. Sustainability, 16:5354.
Bezirhan, U. and von Davier, M. (2023). Automated reading passage generation with openai's large language model. Computers and Education: Artificial Intelligence, 5:100161.
Blonder, R., Feldman-Maggor, Y., and Rap, S. (2024). Are they ready to teach? generative ai as a means to uncover pre-service science teachers' pck and enhance their preparation program. Journal of Science Education and Technology.
Bower, M., Torrington, J., Lai, J. W. M., Petocz, P., and Alfano, M. (2024). How should we change teaching and assessment in response to increasingly powerful generative artificial intelligence? outcomes of the chatgpt teacher survey. Education and Information Technologies, 29:15403–15439.
Brasil (2025). Decreto nº 12.773, de 2025. Dispõe sobre a Política Nacional de Educação Especial na Perspectiva da Educação Inclusiva.
Cavalcante, J. P. S., Apolinário, J. A. F., and Souza, E. P. R. (2024). Como as soluções voltadas para surdos são avaliadas? um estudo apoiado por inteligência artificial generativa. In Anais do I Workshop de Informática na Educação Inclusiva (WIEI 2024), pages 85–92. Sociedade Brasileira de Computação.
Cheah, Y. H., Lu, J., and Kim, J. (2025). Integrating generative artificial intelligence in k-12 education: Examining teachers' preparedness, practices, and barriers. Computers and Education: Artificial Intelligence, 8.
da Costa Silva, J. C. and Ferreira, H. N. M. (2024). Adaptação de questões avaliativas para estudantes neurodivergentes: Uma arquitetura computacional fundamentada em inteligência artificial generativa. In Anais do I Workshop de Informática na Educação Inclusiva (WIEI 2024), pages 36–43. Sociedade Brasileira de Computação.
de Lima, L. J. F. and Benini, F. A. V. (2025). Personalized learning with artificial intelligence: a case study in a literacy extension project. Cuadernos de Educación y Desarrollo, 17:e7744.
Dhungana, D. and Paudel, S. (2025). Personalized learning paths: Automated guidance and monitoring for individual learning experiences. In IEEE EUROCON 2025 - 21st International Conference on Smart Technologies, pages 1–6. IEEE.
dos Santos, D. S., Cardoso, P. C. F., and Pinto, V. H. S. C. (2025). Égua assist: Uma ferramenta de apoio ao ensino de lógica de programação para estudantes com deficiência visual. In Anais do XXXIII Workshop sobre Educação em Computação (WEI 2025), pages 1079–1091. Sociedade Brasileira de Computação - SBC.
Hemalatha, K., Deepika, V., M Mallika, R., and Babu, K. M. (2024). Large language model based personalized learning assistant for career-oriented skills. In 2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), pages 1–6.
Jauhiainen, J. S. and Garagorry Guerra, A. (2024). Generative ai and education: dynamic personalization of pupils' school learning material with chatgpt. Frontiers in Education, Volume 9 - 2024.
Jayaweera, I. (2025). Revolutionizing education: Generative ai as a catalyst for personalized learning and innovative teaching practices. In 2025 5th International Conference on Advanced Research in Computing (ICARC), pages 1–6. IEEE.
Karimy, A. U., Rasuli, J., and Reddy, P. C. (2024). Ai in online educational access: Breaking barriers for female learners. In 2024 21st International Conference on Information Technology Based Higher Education and Training (ITHET), pages 1–9. IEEE.
Kindenberg, B. (2025). The role of ai in historical simulation design: A tpack perspective on a french revolution simulation design experience. Education Sciences, 15:192.
Kitchenham, B. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical report, Ver. 2.3 EBSE Technical Report. EBSE.
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.
Laranjeira, M. L. and Bezerra, P. T. L. (2025). Gerador automático de planos de aula sobre tecnologia baseado em llms. In Anais do XXXIII Workshop sobre Educação em Computação (WEI 2025), pages 515–526. Sociedade Brasileira de Computação - SBC.
Lee, S. and Song, K.-S. (2024). Teachers' and students' perceptions of ai-generated concept explanations: Implications for integrating generative ai in computer science education. Computers and Education: Artificial Intelligence, 7:100283.
Liu, J., Sun, D., Sun, J., Wang, J., and Yu, P. L. H. (2025a). Designing a generative ai enabled learning environment for mathematics word problem solving in primary schools: Learning performance, attitudes and interaction. Computers and Education: Artificial Intelligence, 9:100438.
Liu, R., Pang, W., Chen, J., Balakrishnan, V. A., and Chin, H. L. (2025b). The application of scaffolding instruction and ai-driven diffusion models in children's aesthetic education: A case study on teaching traditional chinese painting of the twenty-four solar terms in chinese culture. Education and Information Technologies, 30:9129–9160.
Makransky, G., Shiwalia, B. M., Herlau, T., and Blurton, S. (2025). Beyond the "wow" factor: Using generative ai for increasing generative sense-making. Educational Psychology Review, 37:60.
Monib, W. K., Qazi, A., Silva, L. D., and Mahmud, M. M. (2024). Exploring learners' experiences with chatgpt in personalized learning. In 2024 6th International Workshop on Artificial Intelligence and Education (WAIE), pages 66–70. IEEE.
Oppenlaender, J., Silvennoinen, J., Paananen, V., and Visuri, A. (2023). Perceptions and realities of text-to-image generation. In 26th International Academic Mindtrek Conference, pages 279–288. ACM.
Petersen, K., Feldt, R., Mujtaba, S., and Mattsson, M. (2008). Systematic mapping studies in software engineering. In 12th International Conference on Evaluation and Assessment in Software Engineering, EASE 2008.
Ravi, P., Masla, J., Kakoti, G., Lin, G. C., Anderson, E., Taylor, M., Ostrowski, A. K., Breazeal, C., Klopfer, E., and Abelson, H. (2025). Co-designing large language model tools for project-based learning with k12 educators. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, pages 1–25. ACM.
Reddy, V. R. K., Tharun, N., Reddy, K. S. R., Hariharan, S., Maddala, B. P., and Baduguna, S. (2025). Student assessment using generative ai by for content specific challenge identification. In 2025 8th International Conference on Trends in Electronics and Informatics (ICOEI), pages 1079–1084. IEEE.
Rethlefsen, M. L. and Page, M. J. (2022). Prisma 2020 and prisma-s: common questions on tracking records and the flow diagram.
Santos, A., Santos, R., and Silva, C. (2025). Teachat: Promovendo o suporte educacional ao autismo com inteligência artificial conversacional. In Anais do XXXIII Workshop sobre Educação em Computação, pages 1370–1380, Porto Alegre, RS, Brasil. SBC.
Shan, R. (2025). Learnrag: Implementing retrieval-augmented generation for adaptive learning systems. In 2025 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), pages 0224–0229. IEEE.
Tasdelen, O. and Bodemer, D. (2025). Generative ai in the classroom: Effects of context-personalized learning material and tasks on motivation and performance. International Journal of Artificial Intelligence in Education.
Uğraş, H., Uğraş, M., Papadakis, S., and Kalogiannakis, M. (2024). Chatgpt-supported education in primary schools: The potential of chatgpt for sustainable practices. Sustainability, 16:9855.
Vygotsky, L. S. (1978). Mind in Society: The Development of Higher Psychological Processes. Harvard University Press, Cambridge, MA. Edited by Michael Cole, Vera John-Steiner, Sylvia Scribner, and Ellen Souberman.
Wang, Z. (2025). Using ai chatbots in visual programming: Effect on programming self-efficacy of upper primary school learners. International Journal of Information and Education Technology, 15:30–38.
Weligodapola, M. and Kumarapperuma, C. U. (2025). Transformative impact of predictive and generative ai on education workforce in developing countries. In 2025 5th International Conference on Advanced Research in Computing. Institute of Electrical and Electronics Engineers Inc.
Wu, H. and Liu, W. (2025). Exploring mechanisms of effective informal genai-supported second language speaking practice: a cognitive-motivational model of achievement emotions. Discover Computing, 28:119.
Yan, Y.-M., Chen, C.-Q., Hu, Y.-B., and Ye, X.-D. (2025). Llm-based collaborative programming: impact on students' computational thinking and self-efficacy. Humanities and Social Sciences Communications, 12:149.
Ye, X., Zhang, W., Zhou, Y., Li, X., and Zhou, Q. (2025). Improving students' programming performance: an integrated mind mapping and generative ai chatbot learning approach. Humanities and Social Sciences Communications, 12:558.
Zha, S., Liu, Y., Zheng, C., Xu, J., Yu, F., Gong, J., and Xu, Y. (2025). Mentigo: An intelligent agent for mentoring students in the creative problem solving process. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, pages 1–22. ACM.
Zhang, X., Xu, S., and Jing, Y. (2025). The mode and practice path of generative artificial intelligence empowerment classroom teaching – based on grounded theory. In Proceedings of the 2025 International Conference on Generative Artificial Intelligence and Digital Media, pages 58–62. ACM.
Abdullahi, M. E., Abdulsalam, M. O., and Ekele, O. A. (2025). The impact of generative ai in personalized learning on students learning outcomes; teachers perception of impact of ai in the 21st century. Babcock University Journal of Education, 10.
Almufarreh, A. (2024). Determinants of students' satisfaction with ai tools in education: A pls-sem-ann approach. Sustainability, 16:5354.
Bezirhan, U. and von Davier, M. (2023). Automated reading passage generation with openai's large language model. Computers and Education: Artificial Intelligence, 5:100161.
Blonder, R., Feldman-Maggor, Y., and Rap, S. (2024). Are they ready to teach? generative ai as a means to uncover pre-service science teachers' pck and enhance their preparation program. Journal of Science Education and Technology.
Bower, M., Torrington, J., Lai, J. W. M., Petocz, P., and Alfano, M. (2024). How should we change teaching and assessment in response to increasingly powerful generative artificial intelligence? outcomes of the chatgpt teacher survey. Education and Information Technologies, 29:15403–15439.
Brasil (2025). Decreto nº 12.773, de 2025. Dispõe sobre a Política Nacional de Educação Especial na Perspectiva da Educação Inclusiva.
Cavalcante, J. P. S., Apolinário, J. A. F., and Souza, E. P. R. (2024). Como as soluções voltadas para surdos são avaliadas? um estudo apoiado por inteligência artificial generativa. In Anais do I Workshop de Informática na Educação Inclusiva (WIEI 2024), pages 85–92. Sociedade Brasileira de Computação.
Cheah, Y. H., Lu, J., and Kim, J. (2025). Integrating generative artificial intelligence in k-12 education: Examining teachers' preparedness, practices, and barriers. Computers and Education: Artificial Intelligence, 8.
da Costa Silva, J. C. and Ferreira, H. N. M. (2024). Adaptação de questões avaliativas para estudantes neurodivergentes: Uma arquitetura computacional fundamentada em inteligência artificial generativa. In Anais do I Workshop de Informática na Educação Inclusiva (WIEI 2024), pages 36–43. Sociedade Brasileira de Computação.
de Lima, L. J. F. and Benini, F. A. V. (2025). Personalized learning with artificial intelligence: a case study in a literacy extension project. Cuadernos de Educación y Desarrollo, 17:e7744.
Dhungana, D. and Paudel, S. (2025). Personalized learning paths: Automated guidance and monitoring for individual learning experiences. In IEEE EUROCON 2025 - 21st International Conference on Smart Technologies, pages 1–6. IEEE.
dos Santos, D. S., Cardoso, P. C. F., and Pinto, V. H. S. C. (2025). Égua assist: Uma ferramenta de apoio ao ensino de lógica de programação para estudantes com deficiência visual. In Anais do XXXIII Workshop sobre Educação em Computação (WEI 2025), pages 1079–1091. Sociedade Brasileira de Computação - SBC.
Hemalatha, K., Deepika, V., M Mallika, R., and Babu, K. M. (2024). Large language model based personalized learning assistant for career-oriented skills. In 2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), pages 1–6.
Jauhiainen, J. S. and Garagorry Guerra, A. (2024). Generative ai and education: dynamic personalization of pupils' school learning material with chatgpt. Frontiers in Education, Volume 9 - 2024.
Jayaweera, I. (2025). Revolutionizing education: Generative ai as a catalyst for personalized learning and innovative teaching practices. In 2025 5th International Conference on Advanced Research in Computing (ICARC), pages 1–6. IEEE.
Karimy, A. U., Rasuli, J., and Reddy, P. C. (2024). Ai in online educational access: Breaking barriers for female learners. In 2024 21st International Conference on Information Technology Based Higher Education and Training (ITHET), pages 1–9. IEEE.
Kindenberg, B. (2025). The role of ai in historical simulation design: A tpack perspective on a french revolution simulation design experience. Education Sciences, 15:192.
Kitchenham, B. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical report, Ver. 2.3 EBSE Technical Report. EBSE.
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.
Laranjeira, M. L. and Bezerra, P. T. L. (2025). Gerador automático de planos de aula sobre tecnologia baseado em llms. In Anais do XXXIII Workshop sobre Educação em Computação (WEI 2025), pages 515–526. Sociedade Brasileira de Computação - SBC.
Lee, S. and Song, K.-S. (2024). Teachers' and students' perceptions of ai-generated concept explanations: Implications for integrating generative ai in computer science education. Computers and Education: Artificial Intelligence, 7:100283.
Liu, J., Sun, D., Sun, J., Wang, J., and Yu, P. L. H. (2025a). Designing a generative ai enabled learning environment for mathematics word problem solving in primary schools: Learning performance, attitudes and interaction. Computers and Education: Artificial Intelligence, 9:100438.
Liu, R., Pang, W., Chen, J., Balakrishnan, V. A., and Chin, H. L. (2025b). The application of scaffolding instruction and ai-driven diffusion models in children's aesthetic education: A case study on teaching traditional chinese painting of the twenty-four solar terms in chinese culture. Education and Information Technologies, 30:9129–9160.
Makransky, G., Shiwalia, B. M., Herlau, T., and Blurton, S. (2025). Beyond the "wow" factor: Using generative ai for increasing generative sense-making. Educational Psychology Review, 37:60.
Monib, W. K., Qazi, A., Silva, L. D., and Mahmud, M. M. (2024). Exploring learners' experiences with chatgpt in personalized learning. In 2024 6th International Workshop on Artificial Intelligence and Education (WAIE), pages 66–70. IEEE.
Oppenlaender, J., Silvennoinen, J., Paananen, V., and Visuri, A. (2023). Perceptions and realities of text-to-image generation. In 26th International Academic Mindtrek Conference, pages 279–288. ACM.
Petersen, K., Feldt, R., Mujtaba, S., and Mattsson, M. (2008). Systematic mapping studies in software engineering. In 12th International Conference on Evaluation and Assessment in Software Engineering, EASE 2008.
Ravi, P., Masla, J., Kakoti, G., Lin, G. C., Anderson, E., Taylor, M., Ostrowski, A. K., Breazeal, C., Klopfer, E., and Abelson, H. (2025). Co-designing large language model tools for project-based learning with k12 educators. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, pages 1–25. ACM.
Reddy, V. R. K., Tharun, N., Reddy, K. S. R., Hariharan, S., Maddala, B. P., and Baduguna, S. (2025). Student assessment using generative ai by for content specific challenge identification. In 2025 8th International Conference on Trends in Electronics and Informatics (ICOEI), pages 1079–1084. IEEE.
Rethlefsen, M. L. and Page, M. J. (2022). Prisma 2020 and prisma-s: common questions on tracking records and the flow diagram.
Santos, A., Santos, R., and Silva, C. (2025). Teachat: Promovendo o suporte educacional ao autismo com inteligência artificial conversacional. In Anais do XXXIII Workshop sobre Educação em Computação, pages 1370–1380, Porto Alegre, RS, Brasil. SBC.
Shan, R. (2025). Learnrag: Implementing retrieval-augmented generation for adaptive learning systems. In 2025 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), pages 0224–0229. IEEE.
Tasdelen, O. and Bodemer, D. (2025). Generative ai in the classroom: Effects of context-personalized learning material and tasks on motivation and performance. International Journal of Artificial Intelligence in Education.
Uğraş, H., Uğraş, M., Papadakis, S., and Kalogiannakis, M. (2024). Chatgpt-supported education in primary schools: The potential of chatgpt for sustainable practices. Sustainability, 16:9855.
Vygotsky, L. S. (1978). Mind in Society: The Development of Higher Psychological Processes. Harvard University Press, Cambridge, MA. Edited by Michael Cole, Vera John-Steiner, Sylvia Scribner, and Ellen Souberman.
Wang, Z. (2025). Using ai chatbots in visual programming: Effect on programming self-efficacy of upper primary school learners. International Journal of Information and Education Technology, 15:30–38.
Weligodapola, M. and Kumarapperuma, C. U. (2025). Transformative impact of predictive and generative ai on education workforce in developing countries. In 2025 5th International Conference on Advanced Research in Computing. Institute of Electrical and Electronics Engineers Inc.
Wu, H. and Liu, W. (2025). Exploring mechanisms of effective informal genai-supported second language speaking practice: a cognitive-motivational model of achievement emotions. Discover Computing, 28:119.
Yan, Y.-M., Chen, C.-Q., Hu, Y.-B., and Ye, X.-D. (2025). Llm-based collaborative programming: impact on students' computational thinking and self-efficacy. Humanities and Social Sciences Communications, 12:149.
Ye, X., Zhang, W., Zhou, Y., Li, X., and Zhou, Q. (2025). Improving students' programming performance: an integrated mind mapping and generative ai chatbot learning approach. Humanities and Social Sciences Communications, 12:558.
Zha, S., Liu, Y., Zheng, C., Xu, J., Yu, F., Gong, J., and Xu, Y. (2025). Mentigo: An intelligent agent for mentoring students in the creative problem solving process. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, pages 1–22. ACM.
Zhang, X., Xu, S., and Jing, Y. (2025). The mode and practice path of generative artificial intelligence empowerment classroom teaching – based on grounded theory. In Proceedings of the 2025 International Conference on Generative Artificial Intelligence and Digital Media, pages 58–62. ACM.
Publicado
05/10/2026
Como Citar
DE SOUZA, Angela Maria; BERTUOL, Vinicius; BORTOLI, André Augusto; MARCOLINO, Anderson da Silva.
Uso de Agentes Conversacionais com IAGen na Personalização do Aprendizado na Educação Básica: uma Revisão Sistemática da Literatura. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 37. , 2026, Goiânia/GO.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 1604-1619.
DOI: https://doi.org/10.5753/sbie.2026.28019.
