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

渴望萌发：情景开发的计算模型：产生新的研究问题以解决关键社会问题的教学法

• 批准号: 2203623
• 负责人: Eduardo Lopez
• 金额: $ 27.46万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2203623&HistoricalAwards=false
• 关键词: EAGER; GERMINATION; Computational; Modeling; Scenario

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.

该项目是通过NSF工程发芽计划资助的，该计划旨在促进教学方法的发展，以提高学术研究人员的能力，并以可能的变革结果提出研究问题和思想。该项目旨在开发和测试一个结构化的创造力框架，通过使用两种技术的结合来识别有影响力和科学严格的研究问题，从而扩大挑战的探索：叙事场景开发和计算建模。尽管场景建模强调了投机和创造力，但计算建模与精度和公式相关。预计利用这种方法的组合将导致研究问题和议程对关键社会挑战产生强大影响。将部署一个针对研究的研究生的试验教学框架，并提供了评估，提供了反馈，以实现迭代性改进。研究生将从一系列学科中招募，并认识到解决关键社会挑战的研究问题的提出可能需要在多种类型的复杂系统和学科之间建立桥梁。该项目可能会产生一种新颖的教学法，该教学法可用于广泛的研究人员，并有望增强其构想社会影响力研究的能力。该项目将开发和试行一年级的多学科研究生课程。有关批判性社会规模挑战的研究问题，这些挑战将情景开发和计算建模。该课程将涉及准实验设计，并将生成纵向，多资源和多准则评估数据。所有学生都将参与着专注于a）审查一组批判性社会挑战的教学模块，b）叙事场景发展以及c）计算建模。在完成A模块之后，学生将分为两组，这些组将在对比序列中进行B和C模块（即B，C，与C相对于B进行B）。每个模块之前和之后，将评估学生产生研究问题的能力。在课程中，对学期的持续监视，学习和调整应导致改进且经过验证的缩放和传播课程。预计这种新颖的教学法会通过测试场景生成的研究问题的新颖性，创造力和定量可行性的能力而产生广泛的影响。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和知识分子优点和评估的支持。更广泛的影响审查标准。