Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/8457
Title: Investigating Student Learning About Disease Spread and Prevention in the Context of Agent-Based Computational Modeling
Authors: Wu, Siyu
Swanson, Hillary
Sherin, Bruce
Wilensky, Uri
Keywords: Learning Sciences
Issue Date: 2022
Publisher: International Society of the Learning Sciences
Citation: Wu, S., Swanson, H., Sherin, B., & Wilensky, U. (2022). Investigating student learning about disease spread and prevention in the context of agent-based computational modeling. In Chinn, C., Tan, E., Chan, C., & Kali, Y. (Eds.), Proceedings of the 16th International Conference of the Learning Sciences - ICLS 2022 (pp. 1245-1248). International Society of the Learning Sciences.
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.
Description: Short Paper
URI: https://dx.doi.org/10.22318/icls2022.1245
https://repository.isls.org//handle/1/8457
Appears in Collections:ISLS Annual Meeting 2022

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