Collaborative Research: Shaping the Future of Science through the Science of Learning
合作研究:通过学习科学塑造科学的未来
基本信息
- 批准号:1745744
- 负责人:
- 金额:$ 0.86万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-10-01 至 2019-03-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The proposed workshop will bring together awardees of the NSF Science of Learning Program. It seeks to capitalize on NSF investments in the Science of Learning to build community among diverse interdisciplinary researchers studying learning, and to build capacity so that investigators can readily reconfigure and mobilize collaborations to capture new opportunities offered by NSF priority areas. As examples, how technology impacts the way we learn and work, as well as how we might harness Big Data to gain greater insight into real-world learning are areas of relevance to the NSF's 10 Big Ideas (https://www.nsf.gov/about/congress/reports/nsf_big_ideas.pdf). This gathering will include researchers from several disciplines under one large umbrella, including neuroscience, cognitive, behavioral and social sciences, computer and information sciences, engineering and education. The proposed effort is needed as there is currently no professional society meeting to support this interdisciplinary Science of Learning community of investigators and their trainees. The gathering seeks to foster information exchange and resource sharing, and to build trust among community members for successful interdisciplinary research. The workshop format will include small group discussions on topics that include new insights and methodologies that offer opportunities to make transformative advances in fundamental knowledge about learning over the lifespan, and intersections in interdisciplinary research that offer opportunities for convergence research in support of NSF's Big Ideas. In this way, the workshop will leverage the group's collective interdisciplinary intelligence for "Big Idea" problem-solving and the unique opportunity to work on problems that are larger than any taken on by individual laboratories. A survey of the research and other needs of the Science of Learning community will be conducted. The diverse disciplinary representation of the participants and the requirement to communicate and discuss science across a broad audience will have broader impacts in building an active and vibrant community capable of addressing complex societal problems through collaborative efforts. In addition, and as part of the workshop, plans will be developed to promote better communication of research findings to educational practitioners, policy makers, and the public. This will help to bridge the gap in understanding between basic research findings and their relevance to social challenges.
拟议的研讨会将汇集学习计划的NSF科学的获奖者。它旨在利用NSF在学习科学方面的投资,在研究学习的不同跨学科研究人员之间建立社区,并建立能力,以便研究人员可以随时重新配置和动员合作,以抓住NSF优先领域提供的新机会。例如,技术如何影响我们的学习和工作方式,以及我们如何利用大数据来更深入地了解现实世界的学习,这些都与NSF的10大想法有关(https://www.nsf.gov/about/congress/reports/nsf_big_ideas.pdf)。这次聚会将包括来自一个大伞下的几个学科的研究人员,包括神经科学,认知,行为和社会科学,计算机和信息科学,工程和教育。建议的努力是必要的,因为目前没有专业的社会会议,以支持这一跨学科的科学学习社区的调查人员和他们的学员。该聚会旨在促进信息交流和资源共享,并为成功的跨学科研究建立社区成员之间的信任。研讨会的形式将包括小组讨论的主题,包括新的见解和方法,提供机会,使变革性的进步,在基础知识的学习寿命,和交叉学科研究,提供机会,融合研究,以支持NSF的大思路。通过这种方式,研讨会将利用该小组的集体跨学科智慧来解决“大创意”问题,并提供独特的机会来解决比单个实验室所承担的任何问题都要大的问题。将对学习科学社区的研究和其他需求进行调查。参与者的不同学科代表性以及在广泛受众中交流和讨论科学的要求将对建立一个能够通过合作努力解决复杂社会问题的积极和充满活力的社区产生更广泛的影响。此外,作为讲习班的一部分,将制定计划,促进更好地向教育工作者、决策者和公众传播研究成果。这将有助于弥合基础研究成果与其对社会挑战的相关性之间的理解上的差距。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Thomas Shipley其他文献
Evaluation of Observationally Based Models Through Salience and Salience Maps
通过显着性和显着性图评估基于观测的模型
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
E. Nelson;Basil Tikoff;Thomas Shipley;Alexander D. Lusk;Cristina Wilson - 通讯作者:
Cristina Wilson
Thomas Shipley的其他文献
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{{ truncateString('Thomas Shipley', 18)}}的其他基金
Collaborative Research: Frameworks: Automated Quality Assurance and Quality Control for the StraboSpot Geologic Information System and Observational Data
合作研究:框架:StraboSpot 地质信息系统和观测数据的自动化质量保证和质量控制
- 批准号:
2311820 - 财政年份:2023
- 资助金额:
$ 0.86万 - 项目类别:
Standard Grant
Supporting Feedback Loop Learning in Natural and Social Science Courses
支持自然科学和社会科学课程中的反馈循环学习
- 批准号:
2142010 - 财政年份:2022
- 资助金额:
$ 0.86万 - 项目类别:
Standard Grant
Collaborative Research: FW-HTF: Integrating Cognitive Science and Intelligent Systems to Enhance Geoscience Practice
合作研究:FW-HTF:整合认知科学和智能系统以增强地球科学实践
- 批准号:
1839705 - 财政年份:2018
- 资助金额:
$ 0.86万 - 项目类别:
Standard Grant
NRI: INT: COLLAB: Co-Robotic Systems for GeoSciences Field Research
NRI:INT:COLLAB:用于地球科学领域研究的协作机器人系统
- 批准号:
1734365 - 财政年份:2017
- 资助金额:
$ 0.86万 - 项目类别:
Standard Grant
SL-CN: Understanding and Promoting Spatial Learning Processes in the Geosciences
SL-CN:理解和促进地球科学中的空间学习过程
- 批准号:
1640800 - 财政年份:2016
- 资助金额:
$ 0.86万 - 项目类别:
Standard Grant
Collaborative Research: FIRE: Making Meaning from Geoscience Data: A Challenge at the Intersection of Geosciences and Cognitive Sciences
合作研究:FIRE:从地球科学数据中获取意义:地球科学和认知科学交叉点的挑战
- 批准号:
1138619 - 财政年份:2011
- 资助金额:
$ 0.86万 - 项目类别:
Standard Grant
An International Workshop on Spatial Cognition and Learning
空间认知与学习国际研讨会
- 批准号:
0823557 - 财政年份:2008
- 资助金额:
$ 0.86万 - 项目类别:
Standard Grant
Collaborative Research: Seismic Reflection Data System for Marine Geosciences II
合作研究:海洋地球科学地震反射数据系统II
- 批准号:
0826282 - 财政年份:2008
- 资助金额:
$ 0.86万 - 项目类别:
Continuing Grant
Enhanced Seismic Data Access System for the University of Texas Institute for Geophysics
德克萨斯大学地球物理研究所增强型地震数据访问系统
- 批准号:
0326679 - 财政年份:2003
- 资助金额:
$ 0.86万 - 项目类别:
Standard Grant
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