Applied Learning for Social Impact: Adapting Toys for Vulnerable Children.

Adapting Toys for Vulnerable Children presents a four-week project-based learning experience within a third-year Electrical and Computer Engineering program, where students apply engineering knowledge to improve accessibility for children with special needs, particularly those with Cerebral Palsy. Working in small teams, students analyze and reverse-engineer commercial toys, identify barriers to interaction, and implement low-cost electronic and electromechanical adaptations that enable alternative methods of activation while preserving the original functionality and play experience. Through this hands-on challenge, students develop technical competencies in embedded systems, circuit analysis, and hardware modification, while also cultivating empathy, teamwork, and awareness of the social impact of engineering solutions. The project demonstrates how applied learning can address real-world inclusion challenges, showing that simple and affordable adaptations can significantly enhance play opportunities and quality of life for vulnerable children

     Nuevos roles del profesorado en tiempos de la IA generativa

Resumen: La inteligencia artificial generativa está transformando la educación y redefiniendo el papel del profesorado, que pasa de transmitir contenidos y evaluar respuestas a diseñar experiencias de aprendizaje, formular problemas relevantes, verificar procesos y fomentar el pensamiento crítico. Esta ponencia mostrará las nuevas posibilidades para personalizar el aprendizaje, automatizar tareas y crear materiales educativos, al tiempo que advierte sobre los retos éticos, los sesgos y la necesidad de desarrollar nuevas competencias para integrar la IA de forma responsable.

     Teaching Agent-Based Manufacturing Under Industry 5.0

Industry 5.0 delineates a socio-technical transformation in manufacturing, conceptualizing a human-centric paradigm that harmonizes advanced cyber-physical architectures with human cognition, systemic resilience, and environmental sustainability. Central to this operational framework is Agent-Based Manufacturing (ABM), a decentralized control architecture wherein autonomous, heterogeneous, and intelligent software agents engage in cooperative decision-making across distributed production networks. As ABM emerges as a critical determinant of next-generation industrial agility, contemporary pedagogical methodologies must be re-engineered to equip learners with the competencies required to architect, optimize, and interface with these multi-agent systems. Educating the industrial workforce in ABM under the strictures of Industry 5.0 necessitates the synthesis of multi-agent system (MAS) theory, distributed artificial intelligence (DAI), cyber-physical production systems (CPPS), and symbiotic human-machine interaction (HMI). Consequently, the formulation of robust, interdisciplinary educational frameworks is imperative to cultivate a highly adaptive, technically proficient workforce capable of sustaining intelligent, self-organizing, and sustainable manufacturing ecosystems.