Improving Students’ Data Literacy in Environmental Science
Improving Students’ Data Literacy in Environmental Science
批准号:
2120998
负责人:
Gregory Teegarden
金额:
$25.88万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-10-01 至 2025-09-30
中文摘要
该项目旨在通过在缅因州圣约瑟夫学院(一所小型私立文理学院)开设环境技术和数据素养辅修课程并对其进行评估,从而提高学生在环境科学方面的数据素养,从而为国家利益服务。增加这门辅修课程是为了提高学生对技术和数据的理解和使用,以解决环境科学中的问题。环境科学家需要具备收集、分析和解释大型数据集的能力,以帮助做出与生态系统相关的明智决策。主动学习技巧已被证明在吸引学生参与课程和帮助学生学习重要概念和技能方面是有效的。该项目将以与公共和私营部门机构的伙伴关系为基础,协助编制本科阶段的环境数据素养技能课程,并采用主动学习技术进行教学。新课程对学生学习的影响将通过调查学生数据素养、技能、能力和自我效能的变化来评估。这门辅修课程可以作为其他本科院校的榜样,这可以帮助增加具有环境科学劳动力所需的数据素养技能的学生人数。该项目的目标是:(1)开发课程以提高学生的数据素养技能;(2)以社区为基础的学习形式为学生提供实地经验和研究机会,使学生能够实践他们的技能。本项目将开设四门新课程,包括环境传感器与网络、大数据集统计、环境数据解释与应用、环境科学技术交流。现有的顶点课程将修改为利用区域公共和私人机构的研究项目侧重于综合环境数据素养技能。该项目将解决两个研究问题:(1)环境技术和数据素养未成年人如何影响数据素养技能能力和自我效能感?(2)数据素养和自我效能感与完成辅修和毕业后的环境科学相关就业或研究生教育之间的关系如何?该研究将采用混合方法,包括使用数据素养技能前后清单评估学生的学习情况,以及使用自我效能调查工具和焦点小组评估自我效能。项目成果将通过会议海报、出版物以及建立和实施讲习班来传播。NSF IUSE: EHR计划支持研究和开发项目,以提高所有学生STEM教育的有效性。通过参与学生学习轨道,该计划支持有前途的实践和工具的创建,探索和实施。该奖项反映了美国国家科学基金会的法定使命,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。
英文摘要
This project aims to serve the national interest by improving students’ data literacy in environmental science through the creation and evaluation of a minor in environmental technology and data literacy at St. Joseph’s College of Maine, a small, private, liberal arts college. The addition of this minor is expected to improve students’ understanding and use of technology and data for the purpose of solving problems in environmental science. Environmental scientists need to have the ability to collect, analyze, and interpret large data sets to help make informed decisions related to ecosystems. Active learning techniques have been shown to be effective in engaging students in courses and helping students learn important concepts and skills. This project will build on partnerships with public- and private-sector institutions to aid in the development of a curriculum in environmental data literacy skills at the undergraduate level that will be taught using active learning techniques. The impact of the new curriculum on student learning will be assessed by investigating changes in students' data literacy skill competencies and self-efficacy. This minor can serve as a model for other undergraduate institutions, which could help increase the number of students with the data literacy skills that are needed in the environmental science workforce.The objectives of this project are to (1) develop courses to improve students’ data literacy skills and (2) provide students with field experiences and research opportunities in a community-based learning format so that students can practice their skills. This project will develop four new courses including Environmental Sensors and Networking, Statistics of Large Data Sets, Interpretation and Application of Environmental Data, and Technical Communication for Environmental Science. An existing capstone course will be modified to focus on integrative environmental data literacy skills using research projects from regional public and private institutions. The project will address two research questions: (1) How does an environmental technology and data literacy minor affect data literacy skill competencies and self-efficacy? (2) How do data literacy and self-efficacy correlate to completion of the minor and post-graduation environmental science related employment or postgraduate education? The study will use a mixed methods approach that will include assessing student learning using a pre- and post-inventory of data literacy skills and assessing self-efficacy using a self-efficacy survey instrument and focus groups. Project results will be disseminated through conference posters, publications, and the creation and implementation of a workshop. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.
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