Sensitivity analysis is the process of attributing the variability of model outputs to uncertainties in input parameters and assumptions. Why is this technique important? Which methods and concepts should be prioritized in teaching it? And what instructional strategies are best suited to different audiences? This work seeks to address these questions by drawing on the experience gained from 12 summer schools conducted by the authors since 1999, along with numerous specialized training courses delivered to academia, research organizations, and international institutions. We aim to distill these experiences into practical guidance for teaching sensitivity analysis, offering both methodological foundations and pedagogical strategies to support educators and future practitioners.
Keywords: global sensitivity analysis; model‐based decision making; pedagogical framework; quantitative modeling education; risk analysis; risk assessment; uncertainty quantification.
© 2026 The Author(s). Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.