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Modeling Social Complexity in Education
SRI and partners are modeling the many components of STEM education and will leverage insights toward development of new methods and tools for sustainable improvement.
The MSCE project works to integrate understandings about complex, adaptive systems with emerging insights from education research, resulting in a framework that takes advantage of recent advances in computational modeling techniques. The project coordinates variables and outcomes across a multitude of research projects, representing them in models aimed at fostering collaborative translational research partnerships with policy, research, education leadership, and industry stakeholders.
The MSCE project is collaborating with Engineering Education and Centers (EEC) principal investigators to ground our work in deep knowledge about engineering education and its dynamics. Individual research projects examining engineering education necessarily focus on critical aspects of a problem whose complexity prevents a single, one-step, “magical bullet” answer. These ‘effects-based’ projects (Maroulis, Guimera, Petry, Stringer, Gomez, Amaral & Wilensky, 2010) focus on understanding particular problems. By virtue of their focus, effect-based studies do not articulate, a priori, theoretical or empirical connections to other projects focusing on other aspects of the complex problem space. A conceptual framework, built on research outcomes, is needed to link extant research efforts and uncover the issues not yet examined by research, and to prioritize research questions that derive from them.
The project is an ongoing collaboration between SRI’s Center for Technology in Learning and The Boeing Company. We have started preliminary work based on Boeing’s examination of STEM education and workforce using system dynamics models with Sandia Laboratories, Science, Technology, Engineering, and Mathematics (STEM) Career Attractiveness System Dynamics Modeling (Sandia Report SAND2008-8049, December, 2008). This work points to the central importance of engineering career attractiveness.
The next step of our work is to understand, with the help of engineering education researchers and practitioners, the dynamics of engineering education as a function of different institutional learning environments, to add information about social networking variables to existing models.
Our meetings will focus on connections across ongoing research, collecting ideas about other research that should be examined, and to begin drafting possible models of the engineering education system and next steps of the project. The project will enable us to asks the following research questions:
- What kinds of predictions are enabled by developing a coordinated framework across extant research outcomes?
- What ‘data’ based on such a framework can inform policy and guide future investment?
This material is based upon work supported by the National Science Foundation under Grant No. 1239830. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.