Active learning techniques to enhance understanding of complex stochastic modeling methods

Applied health economics (HE) builds upon advanced probabilistic and statistical foundations. Complex stochastic methods such as the Monte Carlo simulation are now commonly used in health economic evaluations. However, learning such abstract concepts may prove challenging for students without strong backgrounds in quantitative and statistical methods. This chapter describes an in-class active learning exercise to demonstrate visually the conceptual differences between deterministic and stochastic modeling, as well as between first-order (also known as microsimulation or random walk) and second-order (also known as probabilistic sensitivity analysis) Monte Carlo simulation techniques. The primary objective of this active learning exercise is to improve students’ comprehension and long-term retention of these abstract concepts.