Collaborative Research: NRT-IGE: Employing Model-Based Reasoning in Environmental Science (EMBeRS)
合作研究:NRT-IGE:在环境科学中采用基于模型的推理 (EMBeRS)
基本信息
- 批准号:1545404
- 负责人:
- 金额:$ 27.95万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-09-15 至 2019-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
NRT-IGE: Employing Model-Based Reasoning in Environmental Science (EMBeRS) Scientific synthesis across disciplines is at the heart of addressing important challenges, such as impacts of global change, trade-offs between water, food, and energy production, and the need for sustainable cities. Studies of interdisciplinary research teams indicate that team members struggle to achieve knowledge synthesis across disciplines. Issues arise due to the inability of team members to develop deep knowledge at the frontier of other disciplines and to connect that knowledge with their own expertise to provide a collaborative path forward. The ability to work collaboratively in a research team with others who may hold very different perspectives is a critical aspect of preparing today's students to meet future workforce demands. This National Science Foundation Research Traineeship (NRT) award in the Innovations in Graduate Education (IGE) track is a collaborative project led by the University of Texas at El Paso involving graduate students and faculty from multiple institutions. The project will test a new model for training graduate student teams in environmental sciences to overcome knowledge integration and synthesis challenges. This model will draw on findings from cognitive, learning, and social sciences to develop and test training for graduate students and faculty in model-based reasoning approaches. Model-based reasoning theory posits that humans reason by constructing an internal mental model of the situations, events, and processes that they encounter, and that external representations can be used to facilitate construction of these mental models. External representations include the use of analogies, metaphor, visual models, diagrams and/or other representations for abstraction and communication of complex concepts. In a team setting, these external representations are called boundary negotiating objects. This project will place doctoral students in multidisciplinary teams and facilitate a structured, participatory process that includes a progression of standard, individual, and group model-based reasoning activities as well as instruction on the purposeful co-creation of boundary negotiating objects. Students from multiple institutions will learn together through two-week summer experiences; students who are conducting research in conjunction with larger interdisciplinary teams will be targeted. In addition, the project will train faculty from multiple institutions in the model. The project will examine the implementation by ten faculty members. Survey, interview, and digital data will be collected to examine how graduate students respond to being directly exposed to theories behind the approach as well as the efficacy of the approach as faculty employ it in their graduate classes. This design will allow comparison of the outcomes from guiding students on what to do, versus teaching students why and how to do it. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new, potentially transformative, and scalable models for STEM graduate education training. The Innovations in Graduate Education Track is dedicated solely to piloting, testing, and evaluating novel, innovative, and potentially transformative approaches to graduate education.
NRT-IGE:在跨学科的环境科学(Embers)科学综合中采用基于模型的推理是应对重要挑战的核心,例如全球变化,水,食品和能源生产之间的权衡以及对可持续城市的需求的影响。跨学科研究团队的研究表明,团队成员努力在跨学科中实现知识综合。由于团队成员无法在其他学科的前沿发展深入的知识,并将这些知识与自己的专业知识联系起来,以提供协作途径,因此出现问题。在研究团队中与其他可能具有不同观点的研究团队合作的能力是准备当今学生以满足未来劳动力需求的关键方面。这项国家科学基金会研究训练(NRT)奖研究生教育创新(IGE)曲目是由德克萨斯大学埃尔帕索大学领导的合作项目,涉及多个机构的研究生和教职员工。该项目将测试一种新的模型,以培训环境科学研究生团队,以克服知识整合和综合挑战。该模型将借鉴认知,学习和社会科学的发现,以开发和测试基于模型的推理方法的研究生和教师。基于模型的推理理论认为,人类通过构建他们遇到的情况,事件和过程的内部心理模型来推理,并且可以使用外部表示来促进这些心理模型的构建。外部表示包括使用类比,隐喻,视觉模型,图表和/或其他表示复杂概念的抽象和交流。在团队设置中,这些外部表示称为边界谈判对象。该项目将把博士生置于多学科团队中,并促进一个结构化的参与过程,其中包括标准,基于小组模型的推理活动的进展以及有关边界谈判对象的有目的共同创建的指导。来自多个机构的学生将通过为期两周的夏季经历一起学习;与较大的跨学科团队一起进行研究的学生将成为目标。此外,该项目将培训模型中多个机构的教职员工。该项目将检查十名教职员工的实施。将收集调查,访谈和数字数据,以检查研究生如何应对该方法背后的理论以及教师在研究生课程中采用该方法的疗效。这种设计将使指导学生做什么的结果与教学学生为什么以及如何做的情况进行比较。 NSF研究训练(NRT)计划旨在鼓励开发和实施STEM研究生教育培训的大胆,新,潜在的变革性和可扩展模型。研究生教育轨道的创新仅致力于试点,测试和评估新颖,创新和潜在的变革性研究生教育方法。
项目成果
期刊论文数量(0)
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科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Deana Pennington其他文献
Deana Pennington的其他文献
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{{ truncateString('Deana Pennington', 18)}}的其他基金
Collaborative Research: ABI Development: Transforming Biodiversity Analysis with Landscapes, Automation, and Provenance
合作研究:ABI 开发:通过景观、自动化和来源转变生物多样性分析
- 批准号:
1356707 - 财政年份:2014
- 资助金额:
$ 27.95万 - 项目类别:
Continuing Grant
Collaborative Research: CI-Team Diff: The Virtual Learning Commons: STEM Research Communities Learning about Data Management, Geospatial Informatics, and Scientific Visualization
协作研究:CI-Team Diff:虚拟学习共享空间:STEM 研究社区学习数据管理、地理空间信息学和科学可视化
- 批准号:
1135525 - 财政年份:2011
- 资助金额:
$ 27.95万 - 项目类别:
Standard Grant
CI-TEAM Implementation Project: Collaborative Research: Advancing cyberinfrastructure-based Science Through Education, Training, and Mentoring of Science Communities
CI-TEAM 实施项目:协作研究:通过科学界的教育、培训和指导推进基于网络基础设施的科学
- 批准号:
0753336 - 财政年份:2008
- 资助金额:
$ 27.95万 - 项目类别:
Standard Grant
CI-TEAM Demonstration Project: Advancing Cyberinfrastructure-based Science through Education, Training, and Mentoring of Science Communities
CI-TEAM 示范项目:通过科学界的教育、培训和指导推进基于网络基础设施的科学
- 批准号:
0636317 - 财政年份:2006
- 资助金额:
$ 27.95万 - 项目类别:
Standard Grant
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