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Learning About Diffusion at Two Levels: Agent-based Microscale and Equation-based Macroscale

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Conference

2020 ASEE Virtual Annual Conference Content Access

Location

Virtual On line

Publication Date

June 22, 2020

Start Date

June 22, 2020

End Date

June 26, 2021

Conference Session

Materials Division Technical Session 4

Tagged Division

Materials

Page Count

20

DOI

10.18260/1-2--34897

Permanent URL

https://peer.asee.org/34897

Download Count

423

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Paper Authors

biography

Jacob Kelter Northwestern University

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Jacob Kelter is a PhD student at Northwestern University in the joint program between computer science and learning sciences. His research focuses on using agent-based modeling for science education and computational social science research, both related broadly to complex systems science.

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Jonathan Daniel Emery Northwestern University

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Uri Wilensky Northwestern University

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Uri Wilensky is the Lorraine H. Morton Professor of Learning Sciences, Computer Science and Complex Systems at Northwestern University. He is the founding director of the Center for Connected Learning and Computer-Based Modeling and co-founder of the Northwestern Institute on Complex Systems (NICO). His research interests are in computational science, complex systems, agent-based modeling and integration of computation into K-16 education. He is the author of the award winning NetLogo software, the most widely used agent-based modeling environment. He has published more than 300 scientific papers, and, through the NetLogo models library, has published more than 400 agent-based models across a wide range of content domains. He has also developed many computation-based curricular units for use in K-16 that are used internationally. He is the co-inventor of, and continues to develop restructuration theory that describes the changing content of knowledge in the context of ubiquitous computation, and its implications for making sense of complexity.

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Abstract

Diffusion is a crucial phenomenon in many fields of science and engineering, and it is known to be difficult for students to learn and understand. Ideally, students should understand (1) the micro-level behavior of diffusing atoms or particles, (2) the macro-level patterns of concentration change, along with the accompanying mathematical descriptions, and (3) how these two levels of description are related, i.e. how the macro emerges from the micro. We describe agent-based models (ABMs) of diffusion designed to help students accomplish these learning goals and report the outcomes of implementing them in a university materials science course. The results indicate that the ABM activities helped students understand the micro-level processes of diffusion compared with students from the previous year, but that gaps remained in their understanding of the macro-level patterns of diffusion and the connection between the levels. We conclude with a brief description of our re-designed learning activities to improve outcomes in future years.

Kelter, J., & Emery, J. D., & Wilensky, U. (2020, June), Learning About Diffusion at Two Levels: Agent-based Microscale and Equation-based Macroscale Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--34897

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