Date of Award:
Master of Science (MS)
Instructional Technology and Learning Sciences
The COVID-19 pandemic has highlighted a need for students to learn about public health issues, including the transmission of disease and methods for the prevention of epidemics. This study presents data from a project focused on developing computational microworlds to help middle school students learn about these topics. The microworld is designed to help students model and test their ideas about how a disease spreads through a population and how an epidemic can be prevented. I employed a lab-based case study approach to conduct one-on-one 1.5-hour interviews through Zoom with four middle-school students (ages 12-14). During the interview, the student was asked questions about the spread and prevention of disease and then invited to model and test their ideas in the microworld. This study presents an analysis of students’ pre and post instructional knowledge of disease spread and prevention, which they shared while constructing their initial and later models. I present student ideas in categories of disease transmission, recovery from disease, and disease protection strategies. The paper also analyzes students’ knowledge refinement through the building, testing, and debugging of a disease spread and prevention model. I model student refinement of thinking through steps of building initial models and predicting results, testing initial models, making sense of the results, debugging and retesting models, observing final models, and explaining results, resulting in three types of thinking shifts, and two types of thinking refinements. My findings suggest middle school students can learn about strategies for disease prevention through computational modeling.
Wu, Siyu, "Modeling a Pandemic: Investigating Student Learning about Disease Spread in the Context of Agent-Based Modeling" (2022). All Graduate Theses and Dissertations. 8552.
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