Enhancing the Use of Institutional Data in Projects to Support Low-Income, High-Achieving Students in STEM: Capacity-Building Workshops

加强项目中机构数据的使用，以支持 STEM 领域低收入、成绩优异的学生：能力建设研讨会

• 批准号: 2203148
• 负责人: Amy Chan Hilton
• 金额: $ 4.99万
• 依托单位: University of Southern Indiana
• 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: 2022-01-15 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2203148&HistoricalAwards=false
• 关键词: Enhancing; Use; Institutional; Data; Projects

This project will contribute to the national need for well-educated scientists, mathematicians, engineers, and technicians by empowering STEM faculty members to strengthen their efforts to support low-income STEM students with academic ability and potential to degree completion. The significance of this project is its approach to enhancing the ability and confidence of STEM faculty members in developing data-informed projects through virtual workshops. A total of 50-70 participants from diverse backgrounds and institution types, including faculty members with limited or no S-STEM project experience, will be recruited to two workshop cohorts using intentional strategies. The workshop sessions will incorporate inquiry, reflection, hands-on activities, and practical strategies from experts to help participants meet S-STEM proposal requirements and strengthen their proposal development process. The workshop may serve as a framework for capacity building for faculty in analyzing institutional data related to activities that support low-income STEM students with academic potential.The overall goal of this project is to increase STEM degree completion of low-income, high-achieving undergraduates with demonstrated financial need. In particular, the project goal is to increase faculty investigators’ knowledge of and confidence in using data to better understand their institution’s STEM enrollment, retention, and graduation landscape for low-income students with academic potential and ability. The project scope will support participants in both project development and practical perspectives. The approach intentionally scaffolds participants’ knowledge and skills development through Transparency in Learning and Teaching strategies and practices that foster an inclusive and equity-focused learning environment. The objectives are to: 1) develop and implement a virtual workshop series focused on the data components of an S-STEM proposal; 2) recruit diverse S-STEM teams to one of two offerings of the workshop series; 3) increase participants’ knowledge of and confidence in using institutional data to inform their project; and 4) evaluate the project to identify the needs of faculty PIs in using institutional data and inform improvements in faculty development workshops. For the workshop participants, the anticipated outcomes will include: a) articulating awareness of how institutional data can be used to inform their project plans and goals; b) developing a plan for using student data in project development, including identifying relevant questions that the student data can help answer in alignment with the NSF S-STEM program; and c) drafting a plan for requesting student data from their Institutional Research and Financial Aid offices including IRB considerations. The formative and summative evaluation will identify challenges and promising strategies for gathering, analyzing, and using student data in different institutional contexts. The workshop materials, approach, and results will be disseminated through STEM education conferences and networks and shared with NSF S-STEM leadership. This project is funded by NSF’s Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of low-income academically talented students with demonstrated financial need who earn degrees in STEM fields. It also aims to improve the education of future STEM workers, and to generate knowledge about academic success, retention, transfer, graduation, and academic/career pathways of low-income students.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.

该项目将通过授权 STEM 教员加强努力支持具有学术能力和完成学位潜力的低收入 STEM 学生，从而满足国家对受过良好教育的科学家、数学家、工程师和技术人员的需求。该项目的意义在于它通过虚拟研讨会增强了 STEM 教员开发数据信息项目的能力和信心。来自不同背景和机构类型的总共 50-70 名参与者，包括具有有限或没有 S-STEM 项目经验的教员，将使用有意策略招募到两个研讨会群组。研讨会会议将包含专家的探究、反思、实践活动和实用策略，以帮助参与者满足 S-STEM 提案要求并加强其提案制定流程。该研讨会可以作为教师能力建设的框架，帮助他们分析与支持具有学术潜力的低收入 STEM 学生的活动相关的机构数据。该项目的总体目标是提高具有经济需求的低收入、成绩优异的本科生完成 STEM 学位的数量。特别是，该项目的目标是提高教师调查人员对使用数据的了解和信心，以更好地了解其机构具有学术潜力和能力的低收入学生的 STEM 入学、保留和毕业情况。项目范围将为参与者提供项目开发和实践视角方面的支持。该方法有意通过学习和教学策略和实践的透明度来促进参与者的知识和技能发展，从而营造包容性和注重公平的学习环境。目标是： 1) 开发和实施一个虚拟研讨会系列，重点关注 S-STEM 提案的数据组件； 2) 招募不同的 S-STEM 团队参加研讨会系列的两个课程之一； 3) 提高参与者对使用机构数据为项目提供信息的了解和信心； 4) 评估项目，以确定教师 PI 在使用机构数据方面的需求，并为教师发展研讨会的改进提供信息。对于研讨会参与者来说，预期成果将包括： a) 阐明如何使用机构数据来告知其项目计划和目标； b) 制定在项目开发中使用学生数据的计划，包括确定学生数据可以根据 NSF S-STEM 计划帮助回答的相关问题； c) 起草一份向其机构研究和财政援助办公室索取学生数据的计划，包括 IRB 的考虑因素。形成性和总结性评估将确定在不同机构背景下收集、分析和使用学生数据的挑战和有前途的策略。研讨会材料、方法和结果将通过 STEM 教育会议和网络传播，并与 NSF S-STEM 领导层共享。该项目由 NSF 科学、技术、工程和数学奖学金项目资助，该项目旨在增加具有经济需求的低收入学术天才学生获得 STEM 领域学位的数量。它还旨在改善未来 STEM 工作者的教育，并产生有关低收入学生的学业成功、保留、转学、毕业和学术/职业道路的知识。该奖项反映了 NSF 的法定使命，并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，被认为值得支持。