Leveraging AI Tools in Engineering Education: Promise and Pitfalls of AI in Software Development
Antonio Carlos Bento, José Reinaldo Silva, Marcos R. P. Barretto, Sergio Camacho-León, Elsa Yolanda Torres-Torres
- Journal
- IEEE-RITA
- Autor
- Antonio Carlos Bento, José Reinaldo Silva, Marcos R. P. Barretto, Sergio Camacho-León, Elsa Yolanda Torres-Torres
- Book Title
- Volume
- 21
- Página(s)
- 256-267
- DOI
- 10.1109/RITA.2026.3680777
- Publicada
- 2026
- Month
- Tipo de Documento
- Artigo em Revista
- Abstract
- This paper examines the pedagogical impact of Artificial Intelligence-assisted tools in a university software construction course. Through a 10-week case study with 25 engineering students, the study captures qualitative insights into how students interact with AI tools, the challenges they face, and the learning strategies that emerge. While students reported perceived time savings, the core contribution lies in understanding the educational implications, both positive and challenging of integrating AI into project-based learning environments. The findings reveal that Artificial Intelligence tools enhance prototyping and debugging skills but require structured integration to mitigate over-reliance. The study contributes a framework for balancing Artificial Intelligence use with traditional pedagogy, supporting Sustainable Development Goals 4’s goal of equitable education, while the opinion survey carried out with students shows a result of 96% satisfaction with the use of assisted artificial intelligence tools during the development of the project during the studies.
- Keywords
- Publisher
- IEEE
- URL