Institute in Critical Quantitative, Computational, and Mixed Methods Training For Underrepresented Scholars

为代表性不足的学者提供关键定量、计算和混合方法培训的学院

• 批准号: 1937687
• 负责人: Odis Johnson
• 金额: $ 50.06万
• 依托单位: Washington 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: 2020-01-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1937687&HistoricalAwards=false
• 关键词: Institute; Critical; Quantitative; Computational; Mixed

The project is a collaborative effort lead by Washington University and involving Vanderbilt University, and the University of Pennsylvania to establish an Institute in Critical Quantitative, Computational, and Mixed Methods Training for Underrepresented Scholars. It is designed to mitigate the disparities in the number of underrepresented scholars that utilize quantitative and computational research methods and techniques. The goals are to enable participants to incorporate quantitative and computational methods in conceptualizing research projects, establish collaborative networks of quantitative and computational research practitioners, and affirm self-efficacy of underrepresented faculty through culturally relevant, asset-focused training opportunities. The use of critical perspectives in race/ethnicity responds to a need for more underrepresented scholars to practice critical quantitative approaches in research to complement the larger number who practice critical qualitative approaches.The Institute will provide a continuum of training, individual coaching, and a follow-up proposal development workshop. The project team will conduct an assets assessment of 20 researchers, primarily faculty at minority-serving institutions, recruited to serve as Fellows to establish their baseline needs. The Institute will host a five-day summit to (1) identify possible tensions and transformative practices in using quantitative and computational methods to critically address race and broadening participation in data science and analysis and (2) conduct seminars in data-intensive methods. The curriculum will have a dual focus on core methodological knowledge and specialization and a critical perspective on the use of quantitative and computational methods for research on broadening participation. Topics will include critical theory, research design, fundamentals of quantitative methods, and grant proposal development. The Institute is expected to stimulate more underrepresented researchers to employ quantitative and computational methods in STEM education research. The project is supported through the EHR Core Research: Building capacity in STEM Education Research (EHR: BCSER) competition that is designed to build individuals' capacity to carry out high quality fundamental STEM education research in STEM learning and learning environments, broadening participation in STEM fields, and STEM workforce development.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.

该项目由华盛顿大学牵头，范德比尔特大学和宾夕法尼亚大学参与，旨在为代表性不足的学者建立一个关键定量、计算和混合方法培训研究所。它旨在缓解利用定量和计算研究方法和技术的代表性不足的学者数量的差异。目标是使参与者能够将定量和计算方法纳入研究项目的概念化，建立定量和计算研究从业者的合作网络，并通过与文化相关的、以资产为重点的培训机会，肯定代表性不足的教员的自我效能。在种族/民族中使用批判性视角回应了更多代表性不足的学者在研究中实践批判性定量方法的需求，以补充大量实践批判性定性方法的学者。研训所将提供连续的培训、个别指导和后续建议发展讲习班。项目小组将对20名研究人员进行资产评估，这些研究人员主要是为少数民族服务的机构的教员，他们被聘为研究员，以确定他们的基本需求。该研究所将举办为期五天的峰会，以(1)确定在使用定量和计算方法批判性地解决种族问题和扩大数据科学和分析参与方面可能存在的紧张关系和变革性实践，以及(2)举办数据密集型方法研讨会。该课程将侧重于核心方法论知识和专业化，以及对使用定量和计算方法进行扩大参与研究的批判性观点。主题将包括批判理论，研究设计，定量方法的基础，以及拨款提案的发展。预计该研究所将激励更多代表性不足的研究人员在STEM教育研究中采用定量和计算方法。该项目得到了EHR核心研究：STEM教育研究能力建设（EHR: BCSER）竞赛的支持，该竞赛旨在培养个人在STEM学习和学习环境中开展高质量基础STEM教育研究的能力，扩大STEM领域的参与，以及STEM劳动力的发展。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。