Investigating Student Learning about Disease Spread and Prevention in the Context of Agent-Based Computational Modeling

ABSTRACT

COVID-19 has brought increased attention to the importance of health literacy, including understanding of the transmission and prevention of disease. This study presents data from a project aimed at developing a computational modeling microworld to help middle school students learn about these topics. Specifically, the microworld is meant to help students model and test their ideas about how a disease spreads through a population and how an epidemic can be prevented. The paper analyzes one student's knowledge refinement through the building, testing, and debugging of a disease spread and prevention model. We model student refinement of thinking through steps of building initial models and predicting results, testing initial models and making sense of the results, debugging and retesting models, observing final models, and explaining results. Our findings suggest adolescents can learn about strategies for disease prevention through computational modeling. © ISLS.