The taxonomy of uncertainty in experiential learning: insights from a comparative placemaking course

While exciting to some, grappling with uncertainty in doctoral research can be daunting to many. This paper revisits experiential and group learning in planning education and proposes a framework for understanding how doctoral students initiate research amidst uncertainty. Drawing on Kolb’s experiential learning cycle and Nonaka’s tacit–explicit knowledge creation model, it introduces a four-quadrant framework structured around two intersecting axes: Peirce’s doubt–belief spectrum and Dorst’s frame–value distinction. The framework links four emergent reasoning modes (speculating, discovering, validating, and proving) to four types of inference (abduction-2, abduction-1, induction, and deduction). Speculating reflects high uncertainty and low feasibility; discovering involves moderate uncertainty and feasibility; validating suggests lower uncertainty and higher feasibility; and proving implies both high certainty and high feasibility. The framework emerged through analysing an online doctoral course titled Comparative Placemaking and Urbanism offered in 2023 and 2024. Ten teams across two cohorts completed paired research projects, each adopting one of the four reasoning modes. This experiential learning outcome contributes to planning pedagogy by offering both a conceptual ladder for navigating research uncertainty and a practical diagnostic tool for doctoral supervision.