Polar (DCL- 16-119): Collaborative Research: Computational Guided Inquiry for Incorporating Polar Research into Undergraduate Curricula

极地（DCL-16-119）：协作研究：将极地研究纳入本科课程的计算引导查询

• 批准号: 1712282
• 负责人: Steven Neshyba
• 金额: $ 13.78万
• 依托单位: University of Puget Sound
• 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: 2017-06-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1712282&HistoricalAwards=false
• 关键词: Polar; DCL; 16; 119; Collaborative

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.

该项目将探讨使用计算引导探究（CGI）让本科生以有意义的方式体验极地研究对学生学习的影响。在 CGI 结构的课程中，教师指导学生使用计算工具来管理、分析和可视化数据进行科学探究。该项目将创建一组七个 CGI 模块（例如 Jupyter 笔记本、Excel 电子表格），将极地研究和数据纳入各种本科课程。目的是提高学生的气候素养，提高学生使用真实数据进行科学探究的能力，同时提高课程目标的学习成果。 教师将在夏季研讨会上接受如何在主动学习框架中部署 CGI 模块的培训，然后在各种本科课程（大气科学、化学、物理、环境经济学和计算机科学）中实施这些模块。独立评估将用于探索学习成果。第二次研讨会将解决挑战并改进模块和教学材料，这些模块和教学材料将在教育门户网站上传播。拟议的工作将提高我们对学生如何学习的理解，包括如何通过整合（1）使用真实世界数据（2）课堂翻转的主动学习技术和（3）计算工具来提高学习成果。人们相信使用真实世界的数据集可以真正让学生参与与他们相关的问题。 CGI 模块代表了一种新颖的课程工具，它具有促进跨学科学习的潜力：学生学习课程主题的同时还学习极地数据、如何在查询中使用真实数据以及计算机编程。拟议的工作是测试和评估这些 CGI 模块增强学生学习潜力的第一步。拟议的工作代表了一系列更广泛的影响，包括本科生教育、课程材料开发、主动学习方法的进步以及本科生参与研究。这项工作将通过提高本科生的气候素养、对极地地区及其在气候中的作用的了解以及计算素养来造福社会。此外，学生参与此处提出的主动学习活动所获得的技能预计将在课堂以外的环境中发挥作用。其中包括协作、批判性思维、数据分析和解决问题的技能，这些技能对于帮助学生学会科学地思考复杂挑战的工程解决方案至关重要；这些技能被认为与内容本身一样对于 STEM 教育的成功至关重要。学生参与真实数据和真正的研究工具的探究将有助于将他们的自我认知从被动的学习者转变为有成就的科学家。作为该提案的一部分开发的教育材料将通过来自州立大学、文理学院和社区学院等一系列机构的教师的参与，直接影响各种本科课程。该项目有可能在资助期间惠及大约 1000 名本科生。为了实现更广泛的传播，并在资助期结束后继续接触本科生，所有材料将在在线教育门户网站上共享。

项目成果

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
• 作者: Fortmann, Lea;Beaudoin, Justin;Rajbhandari, Isha;Wright, Aedin;Neshyba, Steven;Rowe, Penny
• 通讯作者: Rowe, Penny