Learning ‘Learning Curves’ with R Shiny

Learning curves are fundamental in understanding individual task performance, with ubiquitous implementation in task assignments, worker scheduling, team formulation, etc., in domains bridging from manufacturing to healthcare. With a broad range of applicability, it is critical that students conceptualize, visualize, and build learning curves to activate that knowledge for effective decision-making. This paper describes a hands-on experiential approach for teaching learning curves that utilizes building LEGO® sets with mathematical formulation and data visualization in an open-source R Shiny application. The R Shiny application was designed to educate and inform students of their curve status while automating the power curve fitting calculations. The proposed methodology appeals and applies to students of all ages and was preliminarily field-tested in two collegiate courses and a K-4 after-school program. This paper introduces this approach and the R Shiny app, while future work includes quantifying improved learning.