Polar (DCL- 16-119): Collaborative Research: Computational Guided Inquiry for Incorporating Polar Research into Undergraduate Curricula
Polar (DCL- 16-119): Collaborative Research: Computational Guided Inquiry for Incorporating Polar Research into Undergraduate Curricula
批准号:
1712282
负责人:
Steven Neshyba
金额:
$13.78万
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
项目状态:
已结题
起止时间:
2017-06-01 至 2022-06-30
中文摘要
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英文摘要
This project will explore impacts on student learning when computational guided inquiry (CGI) is used to allow undergraduate students to experience polar research in a meaningful way. In a CGI-structured course, the instructor guides the students in scientific inquiry using computational tools for managing, analyzing, and visualizing data. This project will create a set of seven CGI modules (e,g, Jupyter notebooks, Excel spreadsheets) that will incorporate polar research and data into a variety of undergraduate classes. The aim is to improve student climate literacy and to increase student ability to use real data to conduct scientific inquiry while at the same time enhancing learning outcomes for course objectives. Instructors will be trained in deploying the CGI modules in an active learning framework in a summer workshop and will then implement the modules in a variety of undergraduate classes (atmosphere science, chemistry, physics, environmental economics, and computer science). Independent evaluation will be used to explore learning outcomes. A second workshop will address challenges and lead to improved modules and instructional material that will be disseminated on an educational website portal.The proposed work will improve our understanding of how students learn, including how learning outcomes can be improved through integration of (1) use of real-world data (2) the active-learning technique of classroom flipping and (3) computational tools. Use of real-world datasets is believed to authentically engage students in questions that are relevant to them. The CGI modules represent a novel curricular tool, which has the potential to foster cross-disciplinary learning: students learn course topics while also learning about polar data, how to use real data in inquiry, and computer programming. The proposed work is a first step in testing and evaluating the potential of these CGI modules to enhance student learning.The proposed work represents a range of broader impacts, including education of undergraduate students, development of course materials, advancement of active learning methods and undergraduate student participation in research. This work will benefit society through increasing climate literacy, understanding of the Polar Regions and their role in the climate, and computational literacy at the undergraduate level. Furthermore, the skills acquired by students engaging in the active learning activities proposed here are expected to be useful in contexts beyond the classroom. These include collaboration, critical thinking, data analysis, and problem solving skills, which are vital in helping students learn to think scientifically about engineering solutions to complex challenges; these skills are believed to be as critical to successful STEM education as the content itself. Student engagement in inquiry with real data and bona fide research tools will help change their self-perceptions from passive learners to realized scientists. The educational materials developed as part of this proposal will directly impact a variety of undergraduate courses through the engagement of instructors from a range of institutions, including state universities, liberal arts colleges, and community colleges. This project has the potential of reaching an estimated 1000 undergraduate students during the grant period. To achieve wider dissemination, and to continue to reach undergraduate students after the grant period ends, all materials will be shared in an online educational portal.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Teaching modules for estimating climate change impacts in economics courses using computational guided inquiry
使用计算引导探究来估计经济学课程中气候变化影响的教学模块
DOI:
10.1080/00220485.2020.1731383
发表时间:
2020
期刊:
The Journal of Economic Education
影响因子:
--
作者:
[Fortmann, Lea, Beaudoin, Justin, Rajbhandari, Isha, Wright, Aedin, Neshyba, Steven, Rowe, Penny]
通讯作者:
Rowe, Penny
Collaborative Research: Polar (NSF 19-601): RUI: Computational Polar ENgagement through GUided INquiry (Computational PENGUIN)
-
批准号:2021213
-
项目类别:Standard Grant
-
资助金额:$9.59万
-
财政年份:2020
-
负责人:Steven Neshyba
-
依托单位:
RUI: Toward a Comprehensive Theory of Mesoscopic Morphology of Ice
-
批准号:1807898
-
项目类别:Standard Grant
-
资助金额:$27.0万
-
财政年份:2018
-
负责人:Steven Neshyba
-
依托单位:
RUI: Scanning electron microscopy and multiscale modeling of mesoscopically rough faceted ice
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批准号:1306366
-
项目类别:Standard Grant
-
资助金额:$19.72万
-
财政年份:2013
-
负责人:Steven Neshyba
-
依托单位:
High Resolution Infrared Radiometry of the Arctic Sky from a Ship-based Platform
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批准号:9712873
-
项目类别:Standard Grant
-
资助金额:$1.89万
-
财政年份:1997
-
负责人:Steven Neshyba
-
依托单位:
NATO Postdoctoral Fellow#
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批准号:8953824
-
项目类别:Fellowship Award
-
资助金额:$4.11万
-
财政年份:1989
-
负责人:Steven Neshyba
-
依托单位:
国内基金
海外基金
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