Collaborative Research: Polar (NSF 19-601): RUI: Computational Polar ENgagement through GUided INquiry (Computational PENGUIN)

合作研究：极地 (NSF 19-601)：RUI：通过引导查询进行计算极地参与（计算企鹅）

• 批准号: 2021429
• 负责人: Penny Rowe
• 金额: $ 20.36万
• 依托单位: NorthWest Research Associates, Incorporated
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2021429&HistoricalAwards=false
• 关键词: Collaborative; Research; Polar; NSF; 19

Researchers from the Northwest Research Associates Inc. and the University of Puget Sound will explore the pedagogical benefits of using computational guided inquiry (CGI) to integrate products of contemporary polar research into undergraduate courses. In CGI-structured learning, the instructor guides students in hands-on scientific inquiry using computational tools for analysis and visualization of data. The PIs propose to develop twelve, 2-3 week undergraduate teaching modules based on the analysis of polar data. The modules will be tested in a variety of undergraduate classrooms, including those at two- and four-year institutions. Students will gain computational skills working with Python programming and with critical thinking and analysis of polar data sets. The proposed work offers a range of broader impacts, including education of undergraduate students, development of new course materials, advancement of active learning methods, and engagement of undergraduate student researchers in polar and pedagogical research. Benefits to society include increasing climate and computational literacy and the understanding of polar regions and their role in the climate. The educational materials developed as part of this proposal will directly impact a variety of undergraduate courses at a range of institutions, including state universities, liberal arts colleges, and community colleges. The project is designed to test whether working directly with polar data via CGI can improve undergraduate climate literacy while enhancing learning outcomes in a variety of undergraduate courses. The work builds on proven educational practices: active learning and guided inquiry. Working with CGI-experienced instructors who will teach the modules, undergraduate researchers and an education research specialist, the PIs will refine the modules, guided by a constructivist framework that includes development of a mental model and hypothesis formulation and testing. An external evaluator will develop questions to measure student knowledge gains and deploy pre- and post-module knowledge surveys. Student survey results will be analyzed to assess knowledge gains and attitudinal shifts. Dissemination to the wider educational community will be accomplished through webinars, conferences, and via the Science Education Resource Center (SERC) educational website portal. This project is funded by the Office of Polar Programs and the Division of Undergraduate Education.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.

西北研究协会公司（Northwest Research Associates Inc.）和普吉特大学（University Puget Sound）的研究人员将探讨使用计算指导性探究（CGI）将当代极地研究的产品整合到本科课程中的教学益处。在CGI结构学习中，讲师使用计算工具来指导学生进行动手科学询问，以分析和可视化数据。 PI提议根据极地数据的分析来开发十二，2-3周的本科教学模块。这些模块将在各种本科教室中进行测试，包括两年和四年制机构的教室。学生将获得与Python编程一起工作的计算技能，并对极地数据集进行批判性思维和分析。拟议中的工作提供了一系列更广泛的影响，包括对本科生的教育，新课程材料的发展，积极学习方法的进步以及本科生研究人员参与极性和教学研究。对社会的好处包括增加气候和计算素养以及对极地地区的理解及其在气候中的作用。作为该提案的一部分开发的教育材料将直接影响各种机构，包括州立大学，文科学院和社区学院的各种本科课程。该项目旨在测试通过CGI直接与Polar Data合作是否可以提高本科气候素养，同时增强各种本科课程的学习成果。这项工作以经过验证的教育实践为基础：积极学习和指导性探究。与CGI经验的讲师一起，他们将教授模块，本科研究人员和教育研究专家，PIS将在建构主义框架的指导下完善模块，其中包括开发心理模型和假设表述和测试。外部评估者将开发疑问，以衡量学生知识的收益并部署模块化前和模块化后知识调查。学生调查结果将进行分析，以评估知识的成就和态度转变。将通过网络研讨会，会议和科学教育资源中心（SERC）教育网站门户来实现向更广泛的教育社区的传播。 该项目由极地计划办公室和本科教育部门提供资金。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响评估标准，被认为值得通过评估来获得支持。