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

该项目将有助于对受过良好教育的科学家，数学家，工程师和技术人员的国家需要，通过支持高成就，低收入学生的保留和毕业，证明在中央佛罗里达大学（UCF）的经济需要。 作为全国最大的大学之一，UCF是招收转学生的前三名机构之一，并被公认为西班牙裔服务机构。 在五年的时间里，该项目将为50名在计算机科学，计算机视觉，计算机工程，数据分析和统计数据科学等人工智能（AI）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。随着BS+MS课程的实施，这些学生中的许多人将能够在完成BS学位后的短短12个月内完成MS学位。所有奖学金获得者将作为转学生进入大学，并将获得支持，直到毕业。这些学生正处于其学术生涯的关键阶段，此时各种各样的障碍最有可能导致学生重新考虑他们的道路，变得容易流失。 每个项目参与者都有一个教师导师，谁在他/她的研究领域的专业知识，和一个同伴导师，谁是在该领域的学位毕业附近。导师作为学生的个人指南，因为他/她在一个新的机构导航未知的领域，并开始具有挑战性的课程。奖学金提供了专注于学习的自由，而无需寻找支付方式的额外负担。总而言之，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，保持他们对学习领域的兴趣，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或雷乌斯，这将是后来用来放置合格的学生进入劳动力。这个项目的总体目标是增加低收入，高成就的学生与证明经济需要的STEM学位完成。 该项目的具体目标是：（i）确保学者在第一年后被保留下来，（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）为转学生提供强烈的归属感，并建立他们作为人工智能学者的身份，（B）通过指导和高级课程来提高学者在人工智能方面的熟练程度，并有可能进行研究和实习，以及（c）在财政支持下提供完成MS学位的明确途径。 预期结果是第一年后的留存率为90%，实习或研究项目参与率为90%，人工智能领域硕士学位课程的录取率为60%。 为确保该项目如期实现其目标，一名外部评估员将监测甄选和征聘过程，沿着毕业率和保留率以及学生和导师活动。 方案成果将通过方案网页、会议报告和文章出版物传播。 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。

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.