EAGER GERMINATION: Computational Modeling from Scenario Development: A Pedagogy for Generating Novel Research Questions to Address Critical Societal Issues

George Mason University, Fairfax VA

Investigators

Abstract

This project is funded through the NSF Directorate for Engineering Germination program, which seeks to foster the development of pedagogical approaches to increase the ability of academic researchers to formulate research questions and ideas with potentially transformative outcomes. This project aims to develop and test a structured creativity framework that broadens exploration of challenges through the identification of impactful and scientifically rigorous research questions using a combination of two techniques: narrative scenario development and computational modeling. While scenario modeling emphasizes speculation and creativity, computational modeling is associated with precision and formulation. Leveraging this combination of approaches is predicted to result in research questions and agendas with strong potential for impact on critical societal challenges. A pilot pedagogical framework for research-focused graduate students will be deployed, with evaluation providing feedback to enable iterative improvement. Graduate students will be recruited from a range of disciplines, recognizing that the formulation of research questions that address critical societal challenges can require creation of bridges between multiple types of complex systems and disciplines. This project could generate a novel pedagogy that would be available and useful to a broad range of researchers, with the promise of enhancing their capacity to conceive societally impactful research. The project will develop and pilot a semester-long, multidisciplinary graduate course on the generation of research questions about critical societal-scale challenges that couples scenario development and computational modeling. The course will involve a quasi-experimental design and will generate longitudinal, multi-source and multi-criteria evaluation data. All students will take part in instructional modules focused on A) Review of a standardized set of critical societal challenges, B) Narrative scenario development, and C) Computational modeling. Subsequent to completion of the A module, students will be divided into two groups which will undertake B and C modules in contrasting sequence (i.e., B then C, versus C then B). Student capacity to generate research questions will be evaluated before and after each module. Continuous monitoring, learning, and adjustment over semesters of course delivery should result in an improved and validated course for scaling and dissemination. This novel pedagogy is anticipated to have broad impact via its capacity to test the novelty, creativity, and quantitative feasibility of scenario-generated research questions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.