Scholarships, Academic, and Social Supports to Provide Low-Income Transfers Students Opportunities for Nurtured Growth in AI

该项目将通过支持中佛罗里达大学（UCF）表现出经济需求的高成就低收入学生的保留和毕业，为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做出贡献。作为全国最大的大学之一，UCF是招收转学生最多的三所大学之一，被公认为西班牙裔服务机构。该项目为期五年，将为50名在计算机科学、计算机视觉、计算机工程、数据分析和统计与数据科学等人工智能领域攻读理学学士（BS）或理学硕士（MS）学位的全日制学生提供奖学金。有了学士+硕士课程，这些学生中的许多人将能够在完成学士学位后的12个月内完成硕士学位。所有奖学金获得者将以转学生的身份进入该项目，并将获得支持，直到毕业。这些学生正处于学术生涯的关键阶段，在这个时期，各种各样的障碍最有可能导致学生重新考虑他们的道路，变得很容易流失。每个项目参与者都有一名在他/她的研究领域具有专业知识的教师导师和一名即将毕业的同行导师。当学生在一个新的机构中摸索未知领域并开始具有挑战性的课程时，导师会作为学生的个人向导。奖学金提供了专注于学习的自由，而没有额外的负担来寻找支付费用的方法。总之，奖学金、导师和志同道合的学生社区的支持，有望减少学生面临的障碍，使他们对自己的研究领域保持兴趣，并激励他们在学业上取得优异成绩。学生将被精简到现有的研究小组或工业实习小组（reu），这些小组随后将用于将合格的学生送入劳动力市场。该项目的总体目标是提高有经济需求的低收入、成绩优异学生的STEM学位完成率。该项目的具体目标是：(i)确保学者在第一年之后被保留下来，（ii）确保学者坚持并完成人工智能高需求领域的学士学位，以及（iii）大幅增加人工智能领域的硕士学位数量。为了实现项目目标，我们将(a)为转校生提供强烈的归属感，并确立他们作为人工智能学者的身份，(b)通过指导和高级课程培养学者对人工智能的熟练程度，具有研究和实习的潜力，以及(c)在经济支持下提供清晰的硕士学位完成途径。预计的结果是，第一年的留校率为90%，实习或研究项目的参与率为90%，人工智能领域硕士学位课程的录取率为60%。为了确保项目能够顺利实现目标，外部评估人员将监督选拔和招聘过程，以及毕业率和保留率，以及学生和导师的活动。项目成果将通过项目网页、会议报告和文章出版物进行传播。该项目由美国国家科学基金会的科学、技术、工程和数学奖学金项目资助，旨在增加有经济需求的低收入学术天才学生在STEM领域获得学位的人数。它还旨在改善未来STEM工作者的教育，并为低收入学生提供有关学业成功、留校、转学、毕业和学术/职业道路的知识。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。

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 the University of Central Florida (UCF). As one of the largest universities in the nation, UCF is among the top three institutions enrolling transfer students and is recognized as a Hispanic Serving Institution. Over its five-year duration, this project will fund scholarships to fifty unique full-time students who are pursuing Bachelor of Science (BS) or Master of Science (MS) degrees in the artificial intelligence (AI) fields of Computer Science, Computer Vision, Computer Engineering, Data Analytics, and Statistics & Data Science. With BS+MS programs in place, many of these students will be able to complete an MS degree in just 12 months after completion of a BS degree. All scholarship recipients will enter the program as transfer students entering the university and will receive support until graduation. These students are at a critical phase in their academic careers, at a time when obstacles of many varieties have the greatest potential to cause students to reconsider their paths, becoming vulnerable to attrition. Each program participant is given a faculty mentor, who has expertise in his/her field of study, and a peer mentor, who is near graduation for a degree in that field. The mentors serve as a personal guides for the student as he/she navigates unknown territory at a new institution and begins challenging coursework. Scholarships provide freedom to focus on studies, without the additional burden of finding ways to pay for it. Altogether, the support of a scholarship, a mentor, and a community of like-minded students, promises to reduce the obstacles students face, keep them interested in their field of study, and motivate them to excel academically. Students will be streamlined into existing research groups or industrial internships or REUs, which will later be used to place qualified students into the workforce.The overall goal of this project is to increase STEM degree completion of low-income, high-achieving students with demonstrated financial need. The specific aims of the project are to (i) ensure scholars are retained past the first year, (ii) ensure scholars persist and complete a BS degree in high-need fields of AI, and (iii) substantially increase the number of MS degrees in AI fields. To achieve the project goals, we will (a) provide transfer students a strong sense of belonging and establish their identities as AI scholars, (b) develop scholars’ proficiency in AI through mentoring and advanced coursework, with potential for research and internships, and (c) provide clear pathways to MS degree completion with financial support. The expected outcomes are 90% retention rate past the first year, 90% participation rate in internships or research projects, and 60% acceptance rate into MS degree programs in AI fields. To ensure the project remains on track for achieving its goals, an external evaluator will monitor the selection and recruitment process, along with graduation and retention rates, as well as student and mentor activities. Program results will be disseminated through the program webpage, reports at conferences and article publication. 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.