Abstract:

Design education plays an important role in preparing engineering students to address complex real-world challenges such as global health and healthcare accessibility. However, traditional engineering education often emphasizes technical knowledge over user-centered problem solving and interdisciplinary collaboration. At the same time, the rapid rise of artificial intelligence (AI) is influencing how students approach ideation, research, and design work, while many educational programs are still adapting to integrate these tools responsibly. These developments highlight the need for pedagogical approaches that combine design-based learning, real healthcare contexts, and critical engagement with AI.

This paper presents a case study of an undergraduate course, Technologies for Sustainable Global Health, at the Singapore University of Technology and Design (SUTD). The course engages engineering students in interdisciplinary design projects addressing real-life healthcare needs in the Singapore local community. Students work in teams to develop technology solutions inspired by real user needs and stakeholder perspectives.

The curriculum integrates concepts in global health, healthcare technology, and frugal innovation with a structured design-based learning approach guided by the Stanford healthcare design framework. The framework provides a systematic process for identifying needs, generating solutions, and evaluating opportunities, supported by online learning resources. Iterative project milestones follow the stages of the framework, guiding students from need identification to concept development and evaluation.

Experiential learning elements include guest lectures from healthcare professionals and global health technology start-up founders, field visits to assistive technology organizations, and engagement with various healthcare stakeholders. To help students navigate the emerging role of AI in design work, the course also incorporates structured activities that encourage reflective and responsible use of AI tools. Students experiment with multiple AI platforms during the ideation process and critically compare the feedback generated by different systems. These exercises help students understand both the potential and the limitations of AI-generated suggestions while maintaining critical thinking in the design process. Guidance is also provided on responsible AI use, including awareness of data security risks, avoiding the disclosure of sensitive design details, and ensuring transparency when citing AI assistance in their work etc.

Student feedback indicates strong engagement with global health topics, hands-on design projects, and AI-supported learning activities. This paper contributes a practice-based pedagogical model for integrating real-world healthcare engagement, structured design frameworks, and reflective AI use in engineering education, with insights transferable to other interdisciplinary design and healthcare innovation courses.

Keywords:

Design-based learning, Global health education, Engineering education, Healthcare innovation, Artificial intelligence in design education, Experiential learning.