Artificial Intelligence Supported Active Learning in Engineering Education
- Ricardo Luiz Perez Teixeira
- Mar 1, 2023
- 3 min read
Updated: Feb 1
Aprendizagem Ativa Apoiada por Inteligência Artificial na Educação em Engenharia
Blog Prof. Ricardo Luiz Perez Teixeira (Engenharia, Inovação e Educação), Itabira, Vol. 6, No. 2 (mar. 2023), eblg001. https://doi.org/10.5281/zenodo.18445199
01/03/2023
Ricardo Luiz Perez Teixeira
Instituto de Engenharias Integradas da Universidade Federal de Itajubá, Itabira, MG, Brazil
Abstract: This topic proposes the reasoning uses of artificial intelligence (AI) in engineering education. Implemented within a real-world university extension project focused on industry demands, the approach frames AI not as an autonomous content generator but as a pedagogical support mechanism. The methodology integrates project-based learning (PBL) principles, where students produce technical reports and educational videos while retaining full responsibility for scientific accuracy and authorship. Observations from the classroom indicate that when AI is used transparently to structure outlines, refine technical language, and organize narratives, it significantly enhances student engagement and the quality of technical synthesis. The primary purpose is to encourage other educators to adopt AI-supported active learning strategies with confidence and ethical awareness.
Keywords: Active learning; Artificial intelligence in education; Materials processing education; Project-based learning; Digital pedagogy.
Selected References:
Teixeira, R. L. P. (2026). Lecture-Based Teaching of Green Steel Concepts. Artefactum – Revista de Estudos Interdisciplinares, 25(1), e2456. https://doi.org/10.23900/artefactum.v25i1.2456 , https://artefactumjournal.com/index.php/artefactum/article/view/2456
Teixeira, R. L. P., Damasceno, A. I. P., Nascimento, R., Vilas Boas, S. B., de Lacerda, J. C., Penha, R. N., Brito, R. F., Hasegawa, H. L., de Brito, T. G., & da Silva, E. M. (2026). Phase stability, microstructural evolution, and corrosion behavior of GTAW-welded AISI 316L austenitic stainless steel. Materials Today Communications, 50, 114537.
Teixeira, R. L. P. (2025). Seminars as catalysts for active learning in a case study of technological university extension projects. Cadernos de Educação, Tecnologia e Sociedade, 18(3), 1062–1075.
Prince, M. (2004). Does active learning work? A review of the research. Journal of Engineering Education, 93(3), 223–231.
UNESCO. (2023). Guidance for generative AI in education and research. Paris: UNESCO.
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.
Project Context: This work is still under development within the framework of UNIFEI, STHEM Brasil, and extension projects. The UNIFEI Prof. Lílian Barros Pereira Campos is at the forefront of innovations that connect theoretical engineering concepts with practical industrial applications. By integrating laboratory case studies with digital artifact creation, the project aims to foster critical thinking and professional communication skills, using AI as a scaffold for learning rather than a replacement for human effort. This topic on "Artificial Intelligence Supported Active Learning in Materials Processing Education" proposes the reasoning uses of artificial intelligence (AI) in engineering education. Guided by faculty mediation and ethical standards, the approach enhances active learning and student synthesis capabilities, highlighting Prof. Ricardo Luiz Perez Teixeira's role as a collaborator in AI, Engineering, and Education initiatives led by Prof. Lilian and other faculty at UNIFEI.
Contend text translated into the Portuguese language
Esta publicação propõe o uso fundamentado da inteligência artificial (IA) como ferramenta de raciocínio na educação em engenharia, conforme detalhado neste Blog, Blog do Prof. Ricardo Luiz Perez Teixeira (Vol. 6, No. 2, março de 2023). Implementada no contexto de um projeto de extensão universitária da UNIFEI alinhado às demandas industriais reais e sob a estrutura do consórcio STHEM Brasil, a abordagem enquadra a IA não como uma geradora autônoma de conteúdo, mas como um mecanismo de suporte pedagógico (scaffolding). A metodologia integra princípios de Aprendizagem Baseada em Projetos (PBL), onde os estudantes produzem relatórios técnicos e vídeos educacionais mantendo total responsabilidade pela precisão científica e autoria . Observações em sala de aula indicam que, quando utilizada de forma transparente para estruturar esboços, refinar a linguagem técnica e organizar narrativas, a IA amplia significativamente o engajamento discente e a qualidade da síntese técnica. O projeto, que conta com a liderança da Profa. Lílian Barros Pereira Campos em inovações que conectam conceitos teóricos a aplicações práticas, e com a colaboração do Prof. Ricardo Luiz Perez Teixeira, visa fomentar o pensamento crítico e habilidades de comunicação profissional, incentivando educadores a adotarem estratégias de aprendizagem ativa apoiadas por IA com confiança e consciência ética.
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