Making the Master's Degree in Artificial Intelligence Accessible to High-Achieving Low-Income Students

让成绩优异的低收入学生能够获得人工智能硕士学位

• 批准号: 2030854
• 负责人: Dimitris Pados
• 金额: $ 100万
• 依托单位: Florida Atlantic University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2030854&HistoricalAwards=false
• 关键词: Making; Master; Degree; Artificial; Intelligence

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 Florida Atlantic University, a Hispanic Serving Institution. The project will support 20-30 college juniors as S-STEM Scholars. Scholars will be selected into two Cohorts and qualify for three-year scholarships to complete an accelerated program to earn a BS in engineering plus an MS in Artificial Intelligence. Accompanying the scholarships, Scholars will have access to a system of evidenced-based best practices designed to enhance their academic performance, persistence, degree completion, and readiness for high quality careers in Artificial Intelligence and related fields. The practices include curricular enhancements (e.g., hierarchical mentoring, undergraduate research) and co-curricular opportunities (e.g., sharing success seminars, internships, financial literacy). This system of practices is designed to build Scholars’ sense of belonging and identities as members of the engineering community, as well as increasing their readiness for STEM careers. The project is intended to bring graduate education in artificial intelligence well within the reach of high-achieving low-income students, thus altering in powerful ways their career trajectories and contribution to STEM. The project will build new knowledge by examining the magnified impact of student scholarships combined with a coordinated system of evidenced-based curricular, co-curricular, and industry-related support on student academic success.The overall goal of this project is to increase STEM degree completion of low-income, high-achieving students with demonstrated financial need. The project will select, provide scholarships to, and support Scholars as they complete the accelerated BS/MS degree program culminating with a masters’ degree in Artificial Intelligence. The project will collect quantitative data on each cohort of Scholars and will use qualitative research approaches to assess Scholars’ satisfaction, motivation, development of personal competencies such as self-efficacy, and workforce preparedness. The project will be evaluated using a mixed methods approach. The project will advance knowledge about how best to prepare the first generations of graduate researchers in artificial intelligence and contribute to the development of a new set of guidelines for preparedness and career entry within this emerging STEM fields and related fields. Project results will be disseminated through professional conferences and publications and a designated project website, as well as through social media and other public awareness channels. 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，证明经济需要在佛罗里达大西洋大学，西班牙裔服务机构。该项目将支持20-30名大学三年级学生作为S-STEM学者。 学者将被分为两个队列，并有资格获得为期三年的奖学金，以完成加速计划，以获得工程学士学位和人工智能硕士学位。伴随着奖学金，学者将有机会获得一个基于证据的最佳实践系统，旨在提高他们的学术成绩，坚持，完成学位，并为人工智能及相关领域的高质量职业做好准备。 这些做法包括课程改进（例如，分层指导，本科生研究）和课外机会（例如，分享成功研讨会、实习、金融知识）。 该实践系统旨在建立学者作为工程社区成员的归属感和认同感，并提高他们对STEM职业的准备。该项目旨在将人工智能研究生教育纳入高成就低收入学生的范围，从而以强有力的方式改变他们的职业轨迹和对STEM的贡献。该项目将通过研究学生奖学金的放大影响，结合循证课程、课外活动和行业相关支持对学生学业成功的协调系统，建立新的知识。该项目的总体目标是提高低收入、高成就、有经济需求的学生的STEM学位完成率。该项目将选择，提供奖学金，并支持学者，因为他们完成加速BS/MS学位课程，最终获得人工智能硕士学位。该项目将收集每个学者群体的定量数据，并将使用定性研究方法来评估学者的满意度，动机，个人能力的发展，如自我效能和劳动力准备。将采用混合方法对该项目进行评价。 该项目将推进有关如何最好地准备第一代人工智能研究生的知识，并有助于制定一套新的指导方针，为这个新兴的STEM领域和相关领域的准备和职业生涯的进入做出贡献。项目成果将通过专业会议和出版物、指定的项目网站以及社交媒体和其他公共宣传渠道传播。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。