Ecological forecasting is an emerging approach which provides an estimate of the future state of an ecological system with uncertainty, allowing society to prepare for changes in important ecosystem services. Ecological forecasts are a powerful test of the scientific method because ecologists make a hypothesis of how an ecological system works; embed their hypothesis in a model; use the model to make a forecast of future conditions; and then when observations become available, assess the accuracy of their forecast, which indicates if their hypothesis is supported or needs to be updated. Consequently, macrosystems ecologists are increasingly using ecological forecasts to predict how ecosystems are changing, but to date there have been few opportunities for receiving training in ecological forecasting at the undergraduate level. Our team is developing teaching modules to teach the foundational concepts  of ecological forecasting to undergraduates with R Shiny apps as part of the Macrosystems EDDIE (Environmental Data-Driven Inquiry & Exploration; MacrosystemsEDDIE.org). We use large, publicly available datasets from NEON and GLEON to engage students in ecology and improve their quantitative reasoning. Each module can be adapted for use in introductory, intermediate, and advanced courses to enhance students' understanding of macrosystems ecology and ecological forecasting. In this workshop, we will provide an overview of the Macrosystems EDDIE modules to interested instructors, as well as lessons learned to aid teaching in both virtual and face-to-face classrooms.