Ill-defined problems in wicked learning environments

Many of today’s global problems are complex and difficult to solve—some may even be impossible. They are characterized by interconnectedness, nonlinear causality, and a lack of clear solutions or definitive answers. Designing for such complex problems is unavoidable, but doing so without understanding biases and the repercussions of one’s design experience and actions compounds its complexity. This article explores what informs designers’ decisions (design cognition) and drives their activities (design behavior) when addressing complex problems and their implications. First, it examines problems through two intersecting theoretical lenses: cognitive psychology and learning. Then, it contextualizes its findings using the co-evolution of design to articulate how designing for complex problems is prone to biases and inaccurate feedback.

keywords: design problems; wicked learning; heuristics; framing

• year: November 2023 — December 2024
• for: She Ji: The Journal of Design, Economics, and Innovation
• download: Article