| Project | Making Sense of Complex Phenomena through Building Object-Based Parallel Models |
| Contact | Uri Wilensky |
| uri@northwestern.edu | |
| URL | http://ccl.northwestern.edu/cm/index.html |
| Project description | Our project is developing tools and curricular materials for students and teachers to use in exploring complex systems. We are using several modeling packages, including Agentsheets, Stella, Model-It and Cocoa, but our concentrated effort right now is invested in object-based parallel modeling tools, most especially StarLogo -- in particular, our extended and enhanced version, StarLogoT1.0, which is available (right now for macintosh only) on our web site. In our work with teachers and students, we have focused on how using the object-based parallel modeling languages has impacted thinking about complex systems, including the patterns of symbolization used to describe such systems. We have also developed a library of "extensible" models that can be used as starting off points for investigation. In our school-based activities, we have looked at 4 levels of use: classroom "demos" and discussions, individual use and exploration of models, individual and group modification and extension of models, and creation of models from "scratch". |
| Theoretical background | The work is informed by a constructionist framework. In particular, the framework of Connected Mathematics guides the work. Questions explored in our research include:• How do the 4 different pedagogy patterns impact learners’ conceptions of complex systems?• To what extent can such modeling and visualization tools lead to qualitative and intuitive understanding of classically counter-intuitive systems phenomena?• What changes do we observe in the patterns of symbolization developed by learners engaged in object-based parallel modeling.?• Can learners advance their understanding of complex phenomena by building extensible object-based models which allow them to engage directly the micro- and macro- features of the phenomena? . In particular, can they: 1) See coherent patterns in and obtain significant insights into complex phenomena that are consistent with insights derived from traditional content domains without beginning with the study of the content domains. 2) Have learning experiences which can contribute to subsequent study of content domains like probability and statistics or differential equations 3) Make sense of phenomena in new and different ways from traditional approaches, allowing topics previously seen as out of reach for high school students to be within their purview.?• Can teachers and researchers use these tools to reconceptualize or re-slice traditional knowledge domains and significantly shift the content of the curriculum?For results of previous work and more on the theoretical background, see http://www.tufts.edu/as/ed/cm/papers/. |
| Challenges | Lots of Technical Challenges:We need to run faster for computationally intensive applications such as kinetic molecular interactions.We need to simplify the modeling language so that the syntax is not a barrier.We need to support multi-level analysis -- right now only two levels of a system can be explored at once. This is a hard problem -- how to make aggregates at one level be objects to feed into the next level?We need multi-platform support. We have a very basic Java version -- but this is not yet satisfactory.We are working on support for multi-user experiments. There are many technical challenges here. |
| Partnership | We could benefit from a technical partner to help solve the problems mentioned above.We would also benefit from educational research expertise on conducting and assessing larger scale experiments. |