Learning Crosscutting Scientific Concepts Through Swarming Behavior and Agent-Based Modeling
The goal of this project is to help students learn complex systems concepts that cut across multiple scientific disciplines in order to provide students with organizing frameworks for science learning. The study of complex systems is an emerging field of science on how interaction among numerous parts of the system gives rise to the overall behavior of the system. Many traditionally segregated science subjects in schools can be unified if taken as complex systems. Complex systems concepts, such as multi-agent, positive feedback, and decentralized control are powerful ideas to understand complex systems across domains. However, these concepts have been shown to be difficult to learn. We achieve this goal by combining Next Generation Science Standard (NGSS) style inquiry process with NetLogo simulation of honeybees' hive-finding behavior--a rich and intriguing phenomenon that embodies multiple complex systems concepts.
NGSS calls for students' meaningful use of scientific practices to develop and evaluate explanatory models of phenomena. BeeSmart revolves around a fun and intriguing phenomenon--a swarm of ten thousand bees can accurately choose the single best hive site from dozens of potential sites available without any leader or coordinator. This phenomenon vividly demonstrates multiple complex systems concepts in action. Presented with NetLogo agent-based models that are based on decades of research on swarm intelligence, students are driven by their curiosity to observe the phenomenon, raise their own questions about the phenomenon, generate hypotheses, verify their hypotheses by manipulating the models, discover the mechanism, and understand the underlying concepts.
BeeSmart is based on Seeley's Honeybee Democracy (2010) (pictured)
BeeSmart Hive-Finding Model is included in the Models Library of NetLogo Version 5.2 and later. For more details about this model or to download it, click Download BeeSmart Hive Finding.
BeeSmart HubNet Model is included in the Models Library of NetLogo Version 5.3.1 and later. For more details about this model or to download it, click Download BeeSmart HubNet. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
BeeSmart web-based participatory simulaiton will be available soon. The curriculum materials can be found here.
Yu (Bryan) Guo and Uri Wilensky
Publications and Presentations
Guo, Y., & Wilensky, U. (2016). Small bugs, big ideas: Teaching complex systems principles through agent-based models of social insects. In C. Gershenson, T. Froese, J. M. Siqueiros, W. Aguilar, E. J. Izquierdo & H. Sayama (Eds.), Proceedings of the Artificial Life Conference 2016 (pp. 664-665). Cambridge, MA: The MIT Press. http://dx.doi.org/10.7551/978-0-262-33936-0-ch105.
Guo, Y., & Wilensky, U. (2016). Learning About Complex Systems with the BeeSmart Participatory Simulation. In proceedings of Constructionism 2016. Bangkok, Thailand. February 1 — 5. http://e-school.kmutt.ac.th/constructionism2016/Constructionism%202016%20Proceedings.pdf
Guo, Y. (2016, August). Teaching Students from Grade School to Grad School about Swarm Intelligence, Evolution, and Other Powerful Ideas with Agent-Based Modeling. Invited talk at the Department of Neurobiology & Behavior and the Department of Ecology & Evolutionary Biology, Cornell University. Ithaca, NY. August 31. 2016
Guo, Y., & Wilensky, U. (2016, June). Investigating student’s difficulties with randomness in complex systems and the affordance of agent-based models as a representational form. Paper presented at the Jean Piaget Society 46th annual meeting. Chicago, IL, June 9 — 11.
Guo, Y., & Wilensky, U. (2016, April). Students’ Difficulties With Randomness in Complex Systems: A Design-Based Research Study. Poster presented at the annual meeting of the American Educational Research Association (Special Interest Group: Learning Sciences), Washington, DC, April 8 – 12.
Guo, Y., & Wilensky, U. (2014). Beesmart: a microworld for swarming behavior and for learning complex systems concepts. Proceedings of the Constructionism 2014 Conference. Vienna, Austria. August 2014.
Guo, Y., & Wilensky, U. (2016). NetLogo BeeSmart – HubNet model. http://ccl.northwestern.edu/netlogo/models/BeeSmartHubNet. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
Guo, Y., & Wilensky, U. (2014). NetLogo BeeSmart - Hive Finding model. http://ccl.northwestern.edu/netlogo/models/BeeSmart-HiveFinding. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
The researchers are greatful for the support from the National Science Fundation (NSF). The BeeSmart Hive Finding phase of the research is supported by NSF DRL Grant # 1020101. The BeeSmart HubNet phase is supported by NSF DRL Grant # 1109834, and the BeeSmart Participatory Simulation Curricular Unit is supported by NSF ITEST Grant # 1614745.