Engineering education requires active methodologies that foster not only the acquisition of technical knowledge but also the development of transversal competencies essential for navigating complex, dynamic, and multidisciplinary professional environments. In this context, we propose a methodological strategy based on the collaborative design of mechanical artefacts as a tool to promote active learning, creativity, critical thinking, and social and environmental awareness.

The proposal is structured around a design competition for students in the Bachelor's Degree in Mechanical Engineering, implemented through Challenge-Based Learning (CBL). This strategy integrates three core pillars: the development of degree-specific competencies, the incorporation of artificial intelligence (AI) tools in the design and project writing process, and alignment with the Sustainable Development Goals (SDGs) as an evaluation criterion.

The challenge is mandatory for students who wish to follow the continuous assessment pathway in the subject Mechanical Technology. Participation in the competition accounts for 10% of the final grade (1 point), provided the complete project is submitted. Teams of 2 to 4 students must deliver a comprehensive project including a technical report, sketches, 3D design, budget, and justification of materials and processes. Autonomous use of AI tools is encouraged throughout all project phases—from idea generation to final documentation—without prior specific training, thereby promoting self-directed learning.

Evaluation is conducted by a panel composed of faculty members and a laboratory technician specialized in mechanical manufacturing, through a deliberative meeting. A detailed rubric is applied with the following weighted criteria: creativity (15%), technical feasibility (25%), economic feasibility (20%), alignment with SDGs (15%), justified use of AI (15%), and overall quality of the report (10%). Additionally, the top three projects receive bonus points added to the final course grade: +1 point for first place, +0.7 for second, and +0.5 for third. These scores contribute to the practical component of the course, which also includes attendance at lab sessions and participation in other projects. To apply these practical scores, students must pass the theoretical written exam.

Furthermore, a qualitative evaluation questionnaire is administered to assess students’ self-perceived learning and competence acquisition in relation to AI, SDGs, and the core competencies of the Mechanical Engineering degree. This methodological proposal is adaptable to other engineering education contexts and represents an innovative pathway to integrate sustainability, emerging technologies, and key competencies into technical university training.

Keywords: Challenge-Based Learning, Transversal skills, Artificial Intelligence, Sustainable Development Goals, Mechanical Engineering.