Enhancing the Use of Institutional Data in Projects to Support Low-Income, High-Achieving Students in STEM: Capacity-Building Workshops
Enhancing the Use of Institutional Data in Projects to Support Low-Income, High-Achieving Students in STEM: Capacity-Building Workshops
批准号:
2203148
负责人:
Amy Chan Hilton
金额:
$4.99万
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
项目状态:
已结题
起止时间:
2022-01-15 至 2024-12-31
中文摘要
该项目将有助于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,使STEM教师能够加强努力,支持低收入STEM学生的学术能力和完成学位的潜力。该项目的重要性在于它的方法,以提高STEM教师的能力和信心,通过虚拟研讨会开发数据知情的项目。来自不同背景和机构类型的50-70名参与者,包括具有有限或没有S-STEM项目经验的教师,将被招募到两个研讨会队列中。研讨会将包括专家的调查,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过程。该研讨会可以作为教师分析与支持低收入STEM学生的活动相关的机构数据的能力建设的框架。该项目的总体目标是提高低收入,高成就的本科生的STEM学位完成证明经济需要。特别是,该项目的目标是增加教师调查人员的知识和信心,使用数据,以更好地了解他们的机构的STEM入学,保留和毕业景观的低收入学生的学术潜力和能力。项目范围将在项目开发和实践方面为参与者提供支持。该方法有意通过促进包容性和注重公平的学习环境的“教学透明”战略和做法,为参与者的知识和技能发展提供支架。其目标是:1)开发和实施一个虚拟研讨会系列,重点关注S-STEM提案的数据组成部分; 2)招募不同的S-STEM团队参加研讨会系列的两个产品之一; 3)增加参与者使用机构数据的知识和信心,以告知他们的项目;以及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。对于研讨会的参与者,预期成果将包括:a)阐明如何利用机构数据为项目计划和目标提供信息的意识; 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帮助回答与NSF S-STEM计划一致的相关问题;以及c)起草一份计划,要求他们的机构研究和财政援助办公室的学生数据,包括IRB的考虑。形成性和总结性评估将确定在不同机构环境中收集,分析和使用学生数据的挑战和有前途的策略。研讨会的材料、方法和结果将通过STEM教育会议和网络传播,并与NSF S-STEM领导层分享。该项目由NSF的科学,技术,工程和数学奖学金计划资助,该计划旨在增加低收入学术人才的数量,这些学生表现出经济需求,并获得STEM领域的学位。它还旨在改善未来STEM工作者的教育,并产生关于低收入学生的学术成功,保留,转移,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。
英文摘要
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.
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会议论文
Capacity-Building for Transforming STEM Education Through Faculty Engagement in Data Analysis and Learning Communities
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批准号:2021532
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项目类别:Standard Grant
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资助金额:$15.0万
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财政年份:2020
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负责人:Amy Chan Hilton
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依托单位:
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财政年份:2004
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负责人:Amy Chan Hilton
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依托单位:
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