Estratégias Pedagógicas e Impactos dos LLMs na Integração Interdisciplinar: Uma Revisão Sistemática
Resumo
Esta Revisão Sistemática da Literatura (RSL) investiga as estratégias pedagógicas e os impactos dos Modelos de Linguagem de Grande Escala (LLMs) na aprendizagem interdisciplinar. Fundamentada no protocolo PRISMA e em auditoria de qualidade rigorosa, a pesquisa analisa o estado da arte da integração da IA em contextos educacionais diversos. Os resultados indicam que a transição de modelos genéricos para arquiteturas especializadas, como a Geração Aumentada por Recuperação (RAG) e sistemas agênticos, é fundamental para assegurar o rigor acadêmico e mitigar alucinações factuais. Observou-se que a orquestração via IA otimiza o planejamento docente em modelos PBL e STEAM, enquanto a agência do estudante é sustentada por mecanismos de suporte digital gradativo e curadoria humana. Conclui-se que a viabilidade da interdisciplinaridade mediada por IA depende da adoção de arquiteturas de alta fidelidade que equilibrem a automação tecnológica com o esforço cognitivo autêntico.
Palavras-chave:
Modelos de Linguagem de Grande Escala, Interdisciplinaridade, Revisão Sistemática da Literatura
Referências
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Sweller, J. (2011). Cognitive Load Theory. Springer.
Yan, L., Sha, L., Zhao, L., Li, Y., Martinez-Maldonado, R., Chen, G., Li, X., Jin, Y., and Gašević, D. (2024). Practical and ethical challenges of large language models in education: A systematic scoping review. British Journal of Educational Technology, 55(1):1–25.
Zhong, C., Ye, F., Wang, Z., Jigeer, A., and Zhan, Z. (2025). Interdisciplinary-qg: An llm-based framework for generating high-quality interdisciplinary test questions with knowledge graphs and chain-of-thought reasoning. In Proceedings of the 14th International Conference on Educational and Information Technology (ICEIT), pages 89–96. IEEE.
Zlotnikova, I., Hlomani, H., Mokgetse, T., and Bagai, K. (2025). Establishing ethical standards for genai in university education: a roadmap for academic integrity and fairness. Journal of Information, Communication and Ethics in Society, 23(2):188–217.
Batista, J., Mesquita, A., and Carnaz, G. (2024). Generative ai and higher education: Trends, challenges, and future directions from a systematic literature review. Information, 15(11):676.
Bou Zakhem, N., Bou Diab, M., and Tahan, S. (2025). A cross-disciplinary academic evaluation of generative ai models in hr, accounting, and economics: Chatgpt-5 vs. deepseek. Administrative Sciences, 15(11):412.
Dermeval, D., Coelho, J. A. P. M., and Bittencourt, I. I. (2020). Mapeamento sistemático e revisão sistemática da literatura em informática na educação. In Jaques, P. A., Siqueira, S., Bittencourt, I., and Pimentel, M., editors, Metodologia de Pesquisa Científica em Informática na Educação: abordagem quantitativa, chapter 3, pages 1–24. SBC, Porto Alegre.
Einarsson, H., Lund, S. H., and Jónsdóttir, A. H. (2024). Application of chatgpt for automated problem reframing across academic domains. Computers and Education: Artificial Intelligence, 6:100194.
Gao, C., Liu, Z., Li, X., and Zhang, L. (2025). Knowledge-augmented generation technology enabling boppps teaching: An example from the triz course. In Procedia Computer Science, volume 266, pages 963–970. Elsevier.
Hassan, A., Tayan, O., Almiladi, A., and Sen, A. A. A. (2025). Ai-enabled assessed learning from an interdisciplinary educational perspective: An empirical case study using chatgpt llm. International Journal of Advanced Computer Science and Applications, 16(11):150–165.
Heilala, J., Shibani, A., and de Freitas, A. G. (2023). The requirements for heutagogical attunement within steam education. International Journal of Emerging Technologies in Learning, 18(16):19–35.
Kitchenham, B. and Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE 2007-001, Keele University and Durham University.
Lazarev, A. and Sedov, D. (2025). Ai scibrief as a gateway to research: A framework for onboarding students into new research areas. In Proceedings of the 5th International Conference on Technology Enhanced Learning in Higher Education (TELE), pages 365–369. IEEE.
Li, Y., Geng, Y., and Yu, X. (2025). Research on a generative ai-enabled system for cultivating interdisciplinary innovative thinking and competencies in applied technology talents. In Proceedings of the 13th International Conference on Orange Technology (ICOT). IEEE.
Lu, J. and Li, J. (2025). A novel framework for educational q&a: Leveraging rag and code interpreters for knowledge retrieval and logical computation. PLoS ONE, 20(12):e0337361.
Pua, L. X., Ramesh, R., Natarajan, P., and Iyer, G. N. (2025). Customaized: Bridging interdisciplinary gaps in ai education with customized content using llms. In Proceedings of the IEEE Global Engineering Education Conference (EDUCON), pages 410–417. IEEE.
Raabe, A. L. A. and Bombasar, J. R. (2020). Mensuração e testes em informática na educação. In Jaques, P. A., Siqueira, S., Bittencourt, I., and Pimentel, M., editors, Metodologia de pesquisa científica em Informática na Educação: abordagem quantitativa, chapter 5, pages 34–50. SBC, Porto Alegre.
Rahimi, M. (2025). Synergising dialogic teaching with competencies-trained genai dialoguing for critical thinking and communication competencies. Journal of University Teaching and Learning Practice, 22(1):45–68.
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 CHI Conference on Human Factors in Computing Systems (CHI '25). ACM.
Shiny Karunya, T., Grace, V. B., Kharmawlong, A., Abisha, A. P., Preha, C., and Wilson, D. D. (2025). Illustrations and interdisciplinary pedagogical implications in brian jacques' selected work using midjourney, chatgpt and dall-e. International Research Journal of Multidisciplinary Scope, 6(3):1067–1079.
Silva, L. et al. (2023). Chatgpt na educação: Um mapeamento sistemático da literatura. In Anais do XXXIV Simpósio Brasileiro de Informática na Educação (SBIE 2023), pages 1245–1256. SBC.
Sreekanth, D., Gopi, S., and Dehbozorgi, N. (2025). Agentic ai quiz-based learning system: Enhancing mcq generation via long-context cached retrieval-augmented generation. In Proceedings of the Frontiers in Education Conference (FIE), pages 215–222. IEEE.
Sweller, J. (2011). Cognitive Load Theory. Springer.
Yan, L., Sha, L., Zhao, L., Li, Y., Martinez-Maldonado, R., Chen, G., Li, X., Jin, Y., and Gašević, D. (2024). Practical and ethical challenges of large language models in education: A systematic scoping review. British Journal of Educational Technology, 55(1):1–25.
Zhong, C., Ye, F., Wang, Z., Jigeer, A., and Zhan, Z. (2025). Interdisciplinary-qg: An llm-based framework for generating high-quality interdisciplinary test questions with knowledge graphs and chain-of-thought reasoning. In Proceedings of the 14th International Conference on Educational and Information Technology (ICEIT), pages 89–96. IEEE.
Zlotnikova, I., Hlomani, H., Mokgetse, T., and Bagai, K. (2025). Establishing ethical standards for genai in university education: a roadmap for academic integrity and fairness. Journal of Information, Communication and Ethics in Society, 23(2):188–217.
Publicado
05/10/2026
Como Citar
DA SILVA, Martony Demes; SOARES, André Castelo Branco.
Estratégias Pedagógicas e Impactos dos LLMs na Integração Interdisciplinar: Uma Revisão Sistemática. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 37. , 2026, Goiânia/GO.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 372-385.
DOI: https://doi.org/10.5753/sbie.2026.27147.
