Journal of Science Education and Technology

, Volume 24, Issue 5, pp 628–647 | Cite as

Comparing Virtual and Physical Robotics Environments for Supporting Complex Systems and Computational Thinking

  • Matthew BerlandEmail author
  • Uri Wilensky


Both complex systems methods (such as agent-based modeling) and computational methods (such as programming) provide powerful ways for students to understand new phenomena. To understand how to effectively teach complex systems and computational content to younger students, we conducted a study in four urban middle school classrooms comparing 2-week-long curricular units—one using a physical robotics participatory simulation and one using a virtual robotics participatory simulation. We compare the two units for their effectiveness in supporting students’ complex systems thinking and computational thinking skills. We find that while both units improved student outcomes to roughly the same extent, they engendered different perspectives on the content. That is, students using the physical system were more likely to interpret situations from a bottom-up (“agent”) perspective, and students using the virtual system were more likely to employ a top-down (“aggregate”) perspective. Our outcomes suggest that the medium of students’ interactions with systems leads to differences in their learning from and about those systems. We explore the reasons for and effects of these differences, challenges in teaching this content, and student learning gains. The paper contributes operationalizable definitions of complex systems perspectives and computational perspectives and provides both a theoretical framework for and empirical evidence of a relationship between those two perspectives.


Computational thinking Systems thinking Robotics Participatory simulations 


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Curriculum and InstructionUniversity of Wisconsin–MadisonMadisonUSA
  2. 2.Departments of Learning Sciences and Computer Science, Center for Connected Learning and Computer-Based Modeling, Northwestern Institute on Complex SystemsNorthwestern UniversityChicagoUSA

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