Cultivating Academic Success in Computing

该项目将通过支持在纽约布鲁克林的长岛大学(刘)留住和毕业有经济需求的高成就低收入学生，来促进全国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。在为期六年的时间里，该项目将为13名正在攻读计算机科学学士学位的全日制学生提供奖学金。三批学生将获得最多四年的奖学金。奖学金获得者及其同龄人将获得由行业合作伙伴参与的全面指导和体验式学习计划，所有这些都旨在帮助学生建立STEM身份，并提高他们对该学科和专业网络的凝聚力。该项目将帮助刘和类似的城市教育机构更好地理解和实施对有才华的低收入计算机科学学生的有效支持战略。该项目的总体目标是增加低收入、高成就、有经济需求的本科生的STEM学位毕业率。它的目的是建设和提高刘布鲁克林计算机科学系在其计算项目中为低收入学生服务的能力，特别是提高有资格获得佩尔助学金的学生的保留率和毕业率。在这一群体中，导致计算机科学毕业率低的挑战包括经济压力，但也包括第一代学生和来自代表性不足群体的学生经常感觉到的对机构、学科和专业网络缺乏凝聚力。该项目将提供全面的、多维度的指导，包括传统的校园咨询、计算机科学教师、行业合作伙伴和近距离同行的指导。它旨在帮助学生发展他们的STEM身份，获得体验式学习和研究机会，并最终在计算机行业或研究生院获得有意义的就业机会。该项目预计将提高所有符合佩尔标准的计算机科学专业学生的四年毕业率(不仅仅是那些获得NSF奖学金的学生)，并建立和维持刘支持未来学生的能力。该项目包括一个全面的评估计划，该计划建立在刘的评估工具和专业知识的基础上，并将促进人们对刘布鲁克林和类似的城市教育机构如何更有效地支持学业优秀的低收入STEM学生的了解。该项目由NSF的科学、技术、工程和数学奖学金项目资助，该项目旨在增加在STEM领域获得学位的低收入学术天才学生的数量。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业成功、留住、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优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project will contribute to the national need for well-educated scientists, mathematicians, engineers, and technicians by supporting the retention and graduation of high-achieving, low-income students with demonstrated financial need at Long Island University (LIU) in Brooklyn, New York. Over its six-year duration, this project will fund scholarships to 13 unique full-time students who are pursuing bachelor’s degrees in Computer Science. Three cohorts of students will receive up to four years of scholarships. Scholarship recipients, along with other students in their cohort, will be offered comprehensive mentoring and experiential learning plans involving industry partners, all with the aim of helping students build a STEM identity and improve their cohesion to the discipline and within professional networks. The project will help LIU and similar urban educational institutions better understand and implement effective support strategies for talented, low-income Computer Science students. The overall goal of this project is to increase STEM degree completion of low-income, high-achieving undergraduates with demonstrated financial need. It aims to build and improve the capacity of the LIU Brooklyn department of Computer Science to serve low-income students in its computing programs, and specifically to increase retention and graduation rates among students who qualify for Pell grants. Challenges leading to low Computer Science graduation rates in this population include financial strain, but also the lack of cohesion that first-generation students and students from under-represented groups often feel with the institution, the discipline, and professional networks. The project will provide comprehensive, multidimensional mentoring involving traditional campus advising, computer science faculty, industry partners, and near-peer mentors. It aims to help students develop their STEM identity, access experiential learning and research opportunities, and ultimately achieve meaningful placement in the computing industry or graduate school. The project expects to improve the four-year graduation rate for all Pell-eligible computer science majors (not just those receiving NSF scholarships), and to build and sustain LIU’s capacity to support future students. The project includes a comprehensive evaluation plan that builds on LIU’s assessment tools and expertise, and will advance knowledge about how LIU Brooklyn and similar urban educational institutions can more effectively support academically talented, low-income STEM students. 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.