EAGER: Modeling Social Complexity In Engineering Education

Sri International, Menlo Park CA

Investigators

Abstract

This engineering education research project funded through the EAGER mechanism seeks to understand the challenges of preparing the next-generation engineering workforce and increasing the number and quality of engineering graduates. The proposal will determine if transformative breakthroughs can be achieved by considering education as a complex, adaptive system. The work proposed may allow the integration of advances in computational modeling, understandings about complex, adaptive systems, and emerging understandings from education research. Such a synthesis of perspectives and knowledge may shed light on understanding the educational system, thus informing more focused public and private investment and policy decisions. The broader significance and importance of this project arises through establishing collaborations and information exchanges between researchers in multiple disciplines. By additionally bringing together researchers, policy makers and industry and community stakeholders it may be possible to develop tools and models that allow these groups collaboratively consider implications of proposed policies or interventions in education. This project overlaps with NSF's strategic goals of transforming the frontiers through preparation of an engineering workforce with new capabilities and expertise. Additionally NSF's goal of innovating for society is enabled by creating results and research that are useful for society by informing educational policy and practices.