Computational techniques have greatly extended the range of problems that can be solved by numerical analysis. However, few tools support the combined practice of collaborative learning and discovery in the computational sciences. This project draws on recent work in embodied cognition, which suggests that the process of building models--particularly models with dynamic visualizations--can aid conceptual understanding in complex problem domains. The researchers will develop a system to support and enhance collaborative discovery by re-representing abstract scientific problems in an embodied way. The proposed system will allow researchers to couple visuo-spatial skills with computational techniques to develop understanding and collaborate in the modeling of complex biological systems. Simultaneously, the project will develop techniques to support collaborative modeling in science and engineering. The project will thus test how theories from embodied cognition can inform interaction design and create explicit knowledge about how collaborative discovery happens in the sciences.
By changing the way abstract scientific problems and techniques are represented, the proposed system will make these scientific problem easier for researchers to understand and manipulate through embodied experience. This re-representation of complex problems may have several benefits: 1) help researchers find solutions to problems that would otherwise take too long or seem too difficult to solve; 2) enhance problem-driven learning approaches in science and engineering disciplines; 3) enable interdisciplinary groups of learners or researchers to come together and work on (and develop a shared representation of) complex problems in a hands-on manner; and 4) make complex science and engineering problems more accessible to everyday citizens. The project may also have significant impacts on emerging interactive technologies by establishing embodied cognition as a framework for interaction design.
