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Ill-defined problems in wicked learning environments

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Many of today’s global problems are complex and difficult, sometimes impossible, to solve. They are characterized by interconnectedness, non-linear causality, and a lack of clear solutions or definitive answers. Designing for such complex problems is unavoidable, but doing so without understanding implicit biases and the repercussions of one’s design experience and actions compounds its complexity. This paper explores what informs designers’ decisions (design cognition) and drives their activities (design behaviour) 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 implicit biases and inaccurate feedback.

keywords: design problems; wicked learning, heuristics; framing