Integrating networked large datasets into undergraduate teaching and research through a collaborative workshop with EREN, NEON and Project EDDIE

通过与 EREN、NEON 和 Project EDDIE 的合作研讨会，将网络大型数据集整合到本科生教学和研究中

• 批准号: 2005443
• 负责人: Matthew Heard
• 金额: $ 10万
• 依托单位: Belmont University
• 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: 2020-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2005443&HistoricalAwards=false
• 关键词: Integrating; networked; large; datasets; into

Large-scale ecological questions are best answered using networked research approaches. Networked research promotes cooperative data collection with standard methods by multiple research teams working at different sites across large areas. Networked research and the large, complex datasets that emerge present new research and teaching opportunities for faculty at smaller, teaching-focused institutions. However, faculty at primarily undergraduate institutions (PUIs) face challenges to engaging independently due to a lack of time, personnel, and financial resources. It is vital that we overcome these barriers so that faculty can provide students with access to networked research experiences that will prepare them for scientific careers. This project brings together faculty from undergraduate teaching-focused institutions, including members of the well-established Ecological Research as Education Network (EREN). EREN will collaborate with experts on the open data provided by the National Ecological Observatory Network (NEON) and researchers and educational material creators from Project EDDIE (Environmental Data-Driven Inquiry & Exploration). Intentional, focused EREN-NEON-EDDIE partnerships will allow these organizations to better meet their shared goal of increased understanding of large-scale ecological phenomena, and will create new teaching materials to improve student data literacy and launch networked research projects. Faculty participants from PUIs will gather for a 3-day/3-night workshop at Belmont University in Nashville, TN, in June 2020 that is focused on three themes: (1) Expand the NEON user community by increasing participation of PUI faculty and students, (2) Develop new teaching modules in collaboration with Project EDDIE leaders based on NEON and EREN datasets that enhance data literacy of undergraduate students, and (3) Identify new complementary research projects using data from both EREN and NEON to address large-scale research questions. The workshop outcomes include open access papers on best practices for improving PUI faculty large dataset skills, meeting generalized student learning goals, and assessment strategies for data literacy in large-scale ecology. At least three new teaching modules centered on NEON or EREN datasets will be developed, tested, and made available. Also, at least three novel EREN networked research project ideas will be developed to use of NEON data and/or collect supplementary data in partnership with NEON to address environmental and ecological questions. Faculty leaders of the teaching modules and research projects will meet again in June 2021 to ensure development, publication, and dissemination of these resources.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.

大规模的生态问题最好用网络化的研究方法来回答。网络化研究促进了多个研究小组在大面积不同地点工作时采用标准方法进行合作数据收集。网络研究和出现的大型复杂数据集为较小的教学机构的教师提供了新的研究和教学机会。然而，教师在主要本科院校（PUI）面临的挑战，独立从事由于缺乏时间，人员和财政资源。至关重要的是，我们克服这些障碍，使教师可以为学生提供访问网络的研究经验，这将为他们的科学生涯做好准备。该项目汇集了来自本科教学机构的教师，包括完善的生态研究教育网络（EREN）的成员。EREN将与国家生态观测网络（氖）提供的开放数据专家以及EDDIE项目（环境数据驱动的调查探索）的研究人员和教育材料创作者合作。EREN-NEON-EDDIE合作伙伴关系将使这些组织能够更好地实现他们的共同目标，即增加对大规模生态现象的理解，并将创建新的教材，以提高学生的数据素养，并启动网络研究项目。来自PUI的教师参与者将于2020年6月在田纳西州纳什维尔的贝尔蒙特大学举行为期3天/3晚的研讨会，重点关注三个主题：（1）通过增加PUI教职员工和学生的参与来扩大氖用户社区，（2）与EDDIE项目领导人合作开发基于氖和EREN数据集的新教学模块，增强本科生的数据素养，（3）利用EREN和氖的数据确定新的互补研究项目，以解决大规模的研究问题。研讨会的成果包括关于提高PUI教师大数据集技能的最佳实践的开放获取论文，满足广义的学生学习目标，以及大规模生态学数据素养的评估策略。将开发、测试并提供至少三个以氖或EREN数据集为中心的新教学模块。此外，至少有三个新的EREN网络研究项目的想法将开发使用氖数据和/或收集补充数据的伙伴关系与氖，以解决环境和生态问题。教学模块和研究项目的教师领导将于2021年6月再次会面，以确保这些资源的开发，出版和传播。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。