abstract
- The growing use of Artificial Intelligence (AI) in education offers both benefits and challenges. AI tools can improve efficiency and enrich the learning experience, but they risk encouraging student over-reliance, which can obstruct the development of critical thinking and problem-solving skills. Especially in engineering, where students are expected to develop technical and solution design skills.This study examines an undergraduate Internet of Things (IoT) course using Challenge-Based Learning (CBL). Students identified a problem in their environment and designed solutions supported by scaffolded tasks that progressively shifted responsibility to students and motivated self-assessment. A case study of a final IoT project and a survey conducted with Computer Science students were used to analyze how a scaffolded CBL framework guides responsible AI use.Findings indicate that when AI is utilized responsibly as a tool to aid for obstacles beyond the syllabus, students engage more deeply, develop stronger technical skills, and concentrate on solution design without limiting creativity due to technical gaps. Intentionally providing a base for initial activities can mitigate cognitive offloading and prevent the lack of development of intended skills. This scaffolded approach offers a path for engineering educators to integrate AI without compromising core learning outcomes.