Fostering Interdisciplinary Community, Belonging, and Success of Low-Income, High-Achieving Mathematics, Computer Science, and Statistics Majors

培养低收入、高成就数学、计算机科学和统计学专业的跨学科社区、归属感和成功

• 批准号: 2221516
• 负责人: Nina White
• 金额: $ 150万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 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: 2022-10-01 至 2028-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2221516&HistoricalAwards=false
• 关键词: Fostering; Interdisciplinary; Community; Belonging; Success

This project will contribute to the national need for scientists and professionals highly trained in quantitative fields by supporting the success and retention of high-achieving, low-income students at the University of Michigan, Ann Arbor. Over its six year duration, the project will provide scholarships to three cohorts of students (45 unique undergraduate students total) who are pursuing bachelor’s degrees in Mathematics, Computer Science, and Statistics. Second-year students and transfer students entering the program will receive financial support through graduation. The project will support scholars through their major and into their post-graduation pursuits via several key activities and structures. These include a project-based, interdisciplinary, summer institute; small learning communities in key second year courses; trained, long-term faculty mentors; project-dedicated academic advisors; and the resources of an established broader STEM scholar program. The project will support students by increasing their sense of belonging, academic success, and financial upward mobility, and the institution and disciplines more broadly will also benefit. As part of the project, faculty will be trained in mentoring students from historically marginalized groups. The course-adjacent learning communities that the project supports will also continue to sustain majors, especially those from groups traditionally underrepresented in STEM, beyond the lifetime of the grant. Most broadly, the three target disciplines will benefit from diversifying the pool of practitioners. While much attention has been paid to Calculus as a gatekeeper to STEM disciplines, this project offers a novel approach in its targeted support for students in courses beyond Calculus. The overall goal of the project is to increase degree completion success (as measured by grades, employment, and graduate program admissions) of low-income, high-achieving undergraduates in Mathematics, Computer Science and Statistics. Specifically, goals of the project include having scholars achieve grade benchmarks in targeted second-year courses, obtain internships, build lasting relationships with mentors, and persist in relevant careers or graduate school in their chosen disciplines. A utilization-focused approach will be used to conduct a formative and summative outcome monitoring evaluation of the project’s duration to (1) document the attainment of project goals and objectives, (2) inform improvements in the implementation process, (3) document student outcome attainment, as well as departmental and institutional impacts, and (4) capture lessons learned to inform knowledge dissemination products. For formative evaluation, the evaluation team will collect scholar feedback in written and focus group format, track overall attendance and participation, and compare different incentive structures for study group participation and their success rates. For summative evaluation, the evaluation team will collect survey data on several validated scales, grade data, course-taking data, and career planning/attainment data, and compare these results with a quasi-experimental, comparable “waitlist” of 45 students. The evaluation team will also track outcomes at the department, discipline, and institutional levels. The grant team will share program results and key lessons at relevant national conferences, within the University, through peer-reviewed publications, and on a project website. 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.

该项目将通过支持密歇根大学安阿伯的高成就、低收入学生的成功和保留，为国家对在定量领域训练有素的科学家和专业人员的需求做出贡献。在其六年的时间里，该项目将提供奖学金给三批学生（共45名独特的本科生），他们正在攻读数学，计算机科学和统计学学士学位。进入该计划的二年级学生和转学生将通过毕业获得经济支持。该项目将通过几个关键活动和结构，支持学者通过他们的专业和进入他们的毕业后追求。这些包括一个基于项目的，跨学科的，暑期学院;在关键的第二年课程的小型学习社区;训练有素的，长期的教师导师;项目专用的学术顾问;和一个既定的更广泛的干学者计划的资源。该项目将通过增加学生的归属感，学术成功和财务向上流动来支持学生，机构和学科也将更广泛地受益。作为该项目的一部分，教师将接受培训，指导来自历史上被边缘化群体的学生。该项目支持的课程邻近学习社区也将继续维持专业，特别是那些传统上在STEM中代表性不足的群体，超过了赠款的使用期限。最广泛地说，这三个目标学科将受益于从业人员库的多样化。虽然微积分作为STEM学科的守门人受到了很大的关注，但该项目为微积分以外的课程的学生提供了一种有针对性的支持。该项目的总体目标是提高数学，计算机科学和统计学方面低收入，高成就本科生的学位完成成功率（以成绩，就业和研究生课程录取为衡量标准）。具体而言，该项目的目标包括让学者在有针对性的第二年课程中达到等级基准，获得实习机会，与导师建立持久的关系，并坚持从事相关职业或在所选学科的研究生院学习。将采用注重利用的方法对项目持续时间进行形成性和总结性成果监测评价，以（1）记录项目目标和目的的实现情况，（2）为实施过程中的改进提供信息，（3）记录学生成果的实现情况以及部门和机构的影响，（4）获取经验教训，为知识传播产品提供信息。在形成性评估方面，评估小组将以书面和焦点小组的形式收集学者的反馈，跟踪总体出席率和参与情况，并比较不同的研究小组参与激励结构及其成功率。对于总结性评估，评估小组将收集几个经过验证的量表的调查数据、年级数据、课程数据和职业规划/成就数据，并将这些结果与45名学生的准实验性、可比性“等待名单”进行比较。评价小组还将跟踪部门、学科和机构各级的成果。赠款小组将在相关的国家会议上，在大学内，通过同行评审的出版物和项目网站上分享项目成果和关键经验教训。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，并提供有关低收入学生的学术成功、保留、转学、毕业和学术/职业途径的知识。该奖项反映了NSF的法定使命，并且通过使用基金会的智力价值和更广泛的影响力审查标准进行评估，被认为值得支持。