Design Thinking, AI, and Learning in Complex STE*M Systems: A Computing Education Perspective

Design Thinking in first-year STE*M education is often framed as a human-centred problem-solving methodology. Yet in contemporary computing classrooms, this process now unfolds within an environment saturated by artificial intelligence. AI is not simply a tool students use; it is part of the cognitive ecology in which learning, creativity, and decision-making take place. AI augments human creativity and expands cognitive reach. However, Educators must be cognisant of the epistemic hierarchies embedded in the Eurocentric forms of reasoning that underpin most AI systems. 

From a systems perspective, Design Thinking can be understood as an adaptive learning strategy for navigating complexity, uncertainty, and ambiguity, essentially, simulating conditions that mirror those found in real-world STE*M practice. The stages of empathising, defining, ideating, prototyping, and testing are not linear steps, but feedback loops through which learners construct meaning, negotiate constraints, and refine judgment. The challenge in first-year computing education is not whether AI should be used in this process, but where, how, and to what pedagogical effect. Educators need to be clear not only on how AI is to be used within the Design Thinking process, but also on the why, when, and to what end, and on whose benefit the outcomes of the AI systems’ outputs are. These critical reasoning skills to evaluate the output of AI systems need to be clearly instilled in students as they process outcomes and why they could be so.

This keynote explores how AI can be deliberately and ethically integrated into Design Thinking pedagogy without displacing human sense-making. AI can support early-stage exploration by broadening problem spaces, surfacing alternative perspectives, and assisting with research synthesis during empathising and defining. In ideation, AI can act as a catalyst for divergent thinking, while in prototyping, it can accelerate iteration and reduce technical barriers. However, the critical phases of framing, value judgement, ethical reasoning, and reflective evaluation must remain human-led, particularly at the first-year level, where epistemic habits are still forming. Essentially, the ethical use of AI is culturally situated in collective ways of knowing. At the first-year level, the ethical use of AI is about co-creating a shared cognitive space, where students, communities, and technologies contribute to meaning-making and problem-solving.

By situating AI as a co-participant rather than an authority in the Design Thinking process, educators can help students develop meta-cognitive awareness, critical judgment, and responsible innovation practices. In this sense, Design Thinking becomes not only a method for solving problems but also a pedagogical scaffold for learning to think, collaborate, and create within AI-augmented STE*M systems.

This keynote draws on several case studies in computing education. It argues that intentionally integrating AI into Design Thinking can strengthen these foundational STE*M skills and competencies, ensuring students are well-prepared to grapple thoughtfully with complex socio-technical challenges rather than optimising solutions. All this is grounded in situated ethics and a pluriversal understanding of technology and collective intelligence.

Dr. Gabriel Tuhafeni Nhinda is an informatics scholar and computing educator at the Namibia University of Science and Technology (NUST), where he serves as a Senior Lecturer in the Faculty of Computing and Informatics. He holds a PhD in Informatics and has taught Design Thinking, Systems Analysis, and Digital Innovation at the undergraduate level since 2015.

His work focuses on Design Thinking in STE*M education, the pedagogical integration of artificial intelligence, cybersecurity awareness, and the development of digital competencies in complex learning environments. He has extensive experience teaching first-year computing students and exploring how emerging technologies, including AI, shape learning, creativity, and ethical judgment. Additionally, he is a proponent of Collaborative Online International Learning (COIL) initiatives, which he has successfully hosted with universities on 3 continents.

Dr. Nhinda has led and participated in national and international projects on digital innovation, 5G entrepreneurship, and ICT capacity development, and has served in governance and leadership roles within the ICT ecosystem. He is actively involved in community-based connectivity initiatives and has contributed to policy-aligned discussions on technology, education, and inclusion.