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.

该项目由美国国家科学基金会工程萌芽计划理事会资助，该计划旨在促进教学方法的发展，以提高学术研究人员提出具有潜在变革性成果的研究问题和想法的能力。该项目旨在开发和测试一个结构化的创造力框架，该框架通过结合使用叙事场景开发和计算建模两种技术来识别有影响力且科学严谨的研究问题，从而扩大对挑战的探索。场景建模强调推测和创造力，而计算建模则与精度和公式化相关。预计利用这种方法组合将产生对关键社会挑战具有强大影响潜力的研究问题和议程。将为以研究为重点的研究生部署一个试点教学框架，并通过评估提供反馈以实现迭代改进。研究生将从一系列学科中招募，认识到解决关键社会挑战的研究问题的制定可能需要在多种类型的复杂系统和学科之间建立桥梁。该项目可以产生一种新颖的教学法，可供广大研究人员使用和使用，并有望提高他们构思具有社会影响力的研究的能力。该项目将开发和试点一门为期一个学期的多学科研究生课程关于将场景开发和计算建模结合起来的关键社会规模挑战的研究问题。该课程将涉及准实验设计，并将生成纵向、多源和多标准的评估数据。所有学生都将参加教学模块，重点关注 A) 回顾一系列标准化的关键社会挑战，B) 叙事场景开发，以及 C) 计算建模。完成 A 模块后，学生将被分为两组，以对比顺序学习 B 和 C 模块（即先 B 然后 C，与 C 然后 B）。学生提出研究问题的能力将在每个模块之前和之后进行评估。对课程交付学期的持续监控、学习和调整应该会改进和验证课程的扩展和传播。这种新颖的教学法预计将通过其测试情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 的法定使命，并通过使用基金会的智力优点和知识进行评估，被认为值得支持。更广泛的影响审查标准。