EAGER: Baseline Library of Undergraduate Metrics on Education and Research (BLUMER)

EAGER：本科生教育和研究指标基线图书馆 (BLUMER)

• 批准号: 2012906
• 负责人: Javed Mostafa
• 金额: $ 30万
• 依托单位: University of North Carolina at Chapel Hill
• 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: 2020-05-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2012906&HistoricalAwards=false
• 关键词: EAGER; Baseline; Library; Undergraduate; Metrics

The scale and outcomes of undergraduate research in the US are poorly understood, in part because they are difficult to track and no standardized metrics exist for measuring them. While existing research has utilized surveys of graduates over time to obtain data on this topic, this method is both expensive and necessarily incomplete. Educational institutions and policymakers therefore rely on incomplete information when making policies that impact or promote undergraduate research activities. Given evidence that undergraduate research experiences impact students’ willingness to undertake graduate study and careers in STEM, as well as continuing challenges to diversity and equity in these fields, more complete data is needed to inform both educational research and effective policymaking. This project addresses the problem by developing standards for measuring and understanding undergraduate research pathways using untapped data sources, including scientific publications by undergraduates and records maintained by the schools at which they study. The initial research dataset of undergraduate research products and outcomes focuses on undergraduate activities in multiple settings: research-focused universities, historically black colleges and universities (HBCUs), and STEM-focused companies. In addition to broadening the information base on undergraduate research available to educational institutions, policymakers, and researchers, this project advances new methods in educational data collection, data management, and dissemination. Preserving the privacy and security of educational records is extremely important and represents a technical challenge for researchers trying to collect and disseminate such data at scale. This project draws inspiration from previous innovations in health data systems that both preserve privacy and allow for responsible research on large-scale real-world data sets.Project aims will be accomplished through the collaborative development and refinement of a data collection protocol, implementation of the data collection protocol across partner institutions, and initial development of a secure, compliant, and usable system for storing and working with data. A systematic literature review on methods for evaluating undergraduate research activities, outputs, and subsequent student outcomes will be conducted at the start of the project. Next, interviews will be conducted with appropriate staff at partner institutions to understand and evaluate their existing practices for tracking undergraduate research. Based on the information gathered through these steps, metrics to answer important questions about undergraduate research outcomes along with a corresponding data collection protocol will be jointly developed with partner institutions. An initial dataset will be collected using the developed protocol, focusing on undergraduate research in the fields of computer science and engineering. The policies, procedures, and research methods found to be most suitable to this work will be published to enable more effective and responsible research of undergraduate activity by the broader research community. Finally, requirements for a system to store and disseminate the data will be developed with the goal of providing a platform for future data collection and research at a national scale, across all undergraduate majors.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.

美国本科生研究的规模和成果人们知之甚少，部分原因是它们难以追踪，也没有标准化的衡量标准。虽然现有的研究已经利用毕业生的调查，随着时间的推移，以获得有关这一主题的数据，这种方法是昂贵的，必然是不完整的。因此，教育机构和决策者在制定影响或促进本科生研究活动的政策时依赖于不完整的信息。有证据表明，本科生的研究经历会影响学生在STEM领域进行研究生学习和职业生涯的意愿，以及这些领域的多样性和公平性面临的持续挑战，因此需要更完整的数据来为教育研究和有效的政策制定提供信息。该项目通过使用未开发的数据源（包括本科生的科学出版物和他们学习的学校保存的记录）制定衡量和理解本科生研究途径的标准来解决这个问题。本科生研究产品和成果的初始研究数据集侧重于多种环境中的本科生活动：以研究为重点的大学，历史上的黑人学院和大学（HBCU）以及以STEM为重点的公司。除了扩大教育机构，决策者和研究人员提供的本科生研究的信息基础，该项目推进了教育数据收集，数据管理和传播的新方法。保护教育记录的隐私和安全极其重要，对于试图大规模收集和传播此类数据的研究人员来说，这是一项技术挑战。该项目的灵感来自于之前在健康数据系统方面的创新，这些创新既保护了隐私，又允许对大规模真实世界数据集进行负责任的研究。项目目标将通过合作开发和完善数据收集协议，在合作机构之间实施数据收集协议，以及初步开发安全，合规，和可用的系统来存储和处理数据。在项目开始时，将对评估本科生研究活动，产出和随后的学生成果的方法进行系统的文献综述。接下来，将与合作机构的适当工作人员进行访谈，以了解和评估他们跟踪本科生研究的现有做法。根据通过这些步骤收集的信息，将与合作机构共同制定指标，以回答有关本科生研究成果的重要问题，沿着相应的数据收集协议。将使用开发的协议收集初始数据集，重点是计算机科学和工程领域的本科生研究。发现最适合这项工作的政策，程序和研究方法将被公布，以使更广泛的研究界对本科生活动进行更有效和负责任的研究。最后，将开发一个存储和传播数据的系统的要求，目标是为未来全国范围内所有本科专业的数据收集和研究提供一个平台。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。