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Research Analytics Using the Higher Education Research and Development Survey (HERD) to Impact Institutional Strategy

研究分析利用高等教育研究与发展调查 (HERD) 影响机构战略

基本信息

批准号：
2215223
负责人：
Baron Wolf
金额：
$ 32.5万
依托单位：
University of Kentucky Research Foundation
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2215223&HistoricalAwards=false
关键词：
Research Analytics Using Higher Education

项目摘要

As funding opportunities for sponsored research and development become more competitive and funding agencies hold research entities more accountable, research support professionals, such as research impact librarians, research data analysts, vice presidents for research, and provosts, need to develop new skills to meet these demands. These skills should help research support professionals make important institutionally-focused decisions to support their research strategy, infrastructure, and create pathways for significant investment. To be effective, techniques should employ advanced data analytics, business intelligence tools, and benchmarking datasets. This project will first collect empirical evidence of promising applications of data for institutional decision-making, benchmarking, and best practices development, and then train a select but diverse group of research support professionals in data-driven decision making and relevant analytical techniques. Growth in the research enterprise, facilitated by strategic data-informed decision making, not only has a positive impact on faculty recruitment and retention but also provides opportunities for expanded student participation in research, strengthens quality graduate programs, and creates economic impact for the local and regional economies. Enhancing these skills to help professional better support research is particularly important for smaller and minority-serving institutions to help them focus their funding requests and remain competitive.The National Science Foundation’s National Center for Science and Engineering Statistics’ annual Higher Education Research and Development (HERD) Survey is one source of benchmark data. This project will conduct a national survey of higher education institutions to collect data on the effective use of the HERD survey data in institutional planning and support. The survey will identify what HERD data are most used and useful as well gather ideas of other data and benchmarks that would be of use to institutions to help make their decisions. Then, the project will host an in-person workshop that will use the SCOPE framework for responsible research evaluation (developed by the International Network of Research Management Societies’ Research Evaluation Working Group, INORMS-REG) to help institutions expand their metrics of research evaluation and make better informed decisions about research funding strategies. This workshop will include analytical training on predictive analytics, analytical tools, data visualization, and network analysis, elevating the skills of research support professionals to focus and grow research at their institutions.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.

随着赞助研究和开发的资助机会变得更具竞争力，资助机构对研究实体更加负责，研究支持专业人员，如研究影响图书馆员，研究数据分析师，研究副总裁和教务长，需要开发新的技能来满足这些需求。这些技能应该帮助研究支持专业人员做出重要的以机构为中心的决策，以支持他们的研究战略，基础设施，并为重大投资创造途径。为了有效，技术应该采用先进的数据分析，商业智能工具和基准数据集。该项目将首先收集数据在机构决策、基准和最佳做法发展方面有前途的应用的经验证据，然后培训一批经过挑选但多样化的研究支助专业人员，使他们掌握数据驱动的决策和相关的分析技术。研究企业的增长，由战略数据知情决策促进，不仅对教师招聘和保留产生积极影响，而且还为扩大学生参与研究提供了机会，加强了高质量的研究生课程，并为当地和区域经济创造了经济影响。提高这些技能，帮助专业人员更好地支持研究，对于小型和少数民族服务机构来说尤为重要，以帮助他们集中资金申请并保持竞争力。美国国家科学基金会国家科学与工程统计中心的年度高等教育研究与发展（HERD）调查是基准数据的一个来源。该项目将对高等教育机构进行一次全国性调查，以收集关于在机构规划和支助中有效利用高等教育机构数据库调查数据的数据。该调查将确定哪些HERD数据是最常用和最有用的，并收集其他数据和基准的想法，这些数据和基准将有助于机构做出决策。然后，该项目将举办一个面对面的研讨会，将使用SCOPE框架进行负责任的研究评估（由国际研究管理协会网络的研究评估工作组，INORMS-REG开发），以帮助机构扩大其研究评估指标，并就研究资助战略做出更明智的决策。该研讨会将包括预测分析、分析工具、数据可视化和网络分析方面的分析培训，提升研究支持专业人员的技能，以关注和发展其机构的研究。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。