Scholarships, Mentoring, and Professional Support to Improve Engineering & Artificial Intelligence Student Success at Community Colleges

该项目将通过支持钱德勒-吉尔伯特社区学院有经济需求的高成就、低收入学生的留校和毕业，为国家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。钱德勒-吉尔伯特社区学院是一家西班牙裔服务机构，位于亚利桑那州凤凰城的东南部山谷，那里有快速增长的高科技制造业。在为期6年的时间里，该项目将为至少48名攻读工程学、工程技术员、人工智能和机器学习学位的独特学生提供奖学金。该项目有可能为国家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，增加高成就、低收入学生的留校率和毕业率。该项目团队计划在收集学生成功数据的同时，培养新一代工程师和人工智能专家。该项目有可能造福社会，将社区中高素质的人员培养成不断增长的高科技劳动力，同时促进工程和人工智能行业更多的种族、民族和性别多样性。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。该项目旨在为马里科帕县提供工程学、人工智能和机器学习方面的专业教育机会。该项目包括三个部分：1)向至少48名学生提供192个奖学金；2)通过提供学术支持来保持获奖者的资格；3)组织和促进课外活动、行业伙伴关系和专业发展。该项目将通过三个指标来衡量：1)参与者完成学位的速度比非参与者更高；2)参与者比他们的同龄人对科学界有更高的归属感；3)学者及其导师完成的每月个人发展计划将导致最多四个学期的课程完成和奖学金资格。项目组计划使用数据收集、调查和统计分析来评估该项目。该项目的成果将通过年度报告、在区域和国家会议上的介绍以及出版物与STEM教育界分享。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 Chandler-Gilbert Community College. Chandler-Gilbert Community College, a Hispanic Serving Institution is in the Southeast valley of Phoenix, Arizona where fast-growing high-tech manufacturing industries reside. Over its 6 year duration, this project will fund scholarships to at least 48 unique students who are pursuing Engineering, Engineering Technician, Artificial Intelligence and Machine Learning degrees. The project has the potential to contribute to the national needs for well-educated scientists, mathematicians, engineers, and technicians by increasing the retention and graduation of high-achieving, low-income students. The project team plans to educate a new generation of engineers and artificial intelligence specialists while collecting student success data. The project has the potential to benefit society by developing highly qualified personnel in the community to a growing high-tech workforce while promoting more racial, ethnic, and gender diversity to the engineering and artificial intelligence industries. The overall goal of this project is to increase STEM degree completion of low-income, high-achieving undergraduates with demonstrated financial need. The project is to make accessible specialized educational opportunities in Engineering, Artificial Intelligence and Machine Learning in Maricopa County. The project has three components: 1) providing 192 scholarships to at least 48 students; 2) maintaining the eligibility of the recipients by providing academic support; 3) organizing and facilitating extracurricular events, industry partnerships, and professional development. The project will be measured through three indicators: 1) participants will complete their degrees at a higher rate than non-participants; 2) participants will have a higher sense of belonging to the scientific community than their peers; 3) the monthly individual development plan completed by the scholars and their mentors will lead to course completion and scholarship eligibility through up to four semesters. The project team plans to evaluate the project using data collection, surveys, and statistical analysis. The results of the project will be shared with the STEM education community through annual reports, presentations at regional and national conferences, as well as publications. 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.