Community, Identity, and Competence: Supporting Low-Income Students in Computing and the Data Sciences at the University of Connecticut
Community, Identity, and Competence: Supporting Low-Income Students in Computing and the Data Sciences at the University of Connecticut
批准号:
2322495
负责人:
Daniel Burkey
金额:
$249.94万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2024
资助国家:
美国
项目状态:
未结题
起止时间:
2024-01-01 至 2029-12-31
中文摘要
该项目将有助于区域和国家对计算和数据科学毕业生的需求,并将提高康涅狄格大学(UConn)这些专业的低收入和第一代学生的保留率和毕业率。在为期6年的资助期间,将为三批学生提供服务,在项目生命周期内共有28名S-STEM学者。该项目的学生将作为一年级学生参加介绍性支持课程。在教师和同行导师的帮助下,学者将改善他们的研究经验,职业准备和创业精神;所有这些都将导致积极的毕业后成果,包括全职就业或研究生学习。该项目有可能扩大高等教育的机会,以广泛的学生群体,也将产生知识和最佳实践,支持STEM专业的学习计划。通过与雇用计算和数据科学专业的当地和区域公司合作,该项目还促进了学术界和工业界之间的伙伴关系,并支持当地和国家在计算和数据科学方面的劳动力发展工作,该项目将从康州大学两所学校的八个专业招募符合条件的学生,并让他们参与到高等教育中,高质量的课程设计,旨在提高保留率和毕业率,建立社区,促进STEM身份,并通过体验式学习机会培养学生的能力。被选为S-STEM学者的学生将参与PI开发的各种编程。共同努力,并在文学的坚实基础,文学艺术与科学学院(CLAS),工程学院(SOE)和学生成功研究所(ISS)将专注于三个基础活动:队列形成,基于学科的探索和学术支持,和指导。这些活动反过来又支持该项目旨在向S-STEM学者灌输的三个核心价值观:社区,身份和能力。队列形成的核心是S-STEM学生成功课程,形成了与S-STEM学者早期接触的框架。本课程将建立S-STEM学者作为一个队列,并支持学生的社区和身份的发展。学者们将通过研究机会,实习或合作以及毕业后准备探索不同的途径和技能发展,所有这些都将培养学生作为STEM从业者的能力。所有这些活动都通过一个电子文件夹记录下来,该文件夹支持学生构建他们的知识和身份,同时为课程评估和知识生成提供了一个强大的工具。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。
英文摘要
This project will contribute to the regional and national need for graduates in computing and data science and will increase both the retention and graduation rates for low-income and first-generation students in these majors at the University of Connecticut (UConn). Over the 6-year duration of the grant, three cohorts of students will be served, for a total of 28 S-STEM scholars over the project lifetime. Students in the project will participate in an introductory support course as first-year students. With the help of faculty and peer mentors, scholars will improve their research experiences, career readiness, and entrepreneurship; all of which will lead to positive post-graduation outcomes, including full-time employment or post-graduate studies. This project has the potential to expand access to higher education to a broad group of students and will also generate knowledge and best practices in supporting STEM majors in their programs of study. By partnering with local and regional companies that hire computing and data science majors, this project also fosters partnerships between academia and industry and supports the local and national workforce development efforts in computing and data sciences, areas critical to the national interest.This project will recruit eligible students from eight majors across two schools at UConn and engage them in high-quality programming designed to improve retention and graduation rates, build community, promote STEM identity, and develop students’ competence through experiential learning opportunities. Students selected as S-STEM Scholars will engage with a variety of programming developed by the PIs. Working together and with a strong foundation in the literature, the College of Liberal Arts and Sciences (CLAS), the School of Engineering (SOE), and the Institute for Student Success (ISS) will focus on three foundational activities: Cohort Formation, Discipline-Based Exploration and Academic Support, and Mentoring. These activities in turn support the three core values the project aims to instill in its S-STEM Scholars: Community, Identity, and Competence. At the heart of cohort formation is the S-STEM Student Success course that forms the framework of early engagement with S-STEM Scholars. This course will establish the S-STEM Scholars as a cohort and support students’ development of community and identity. The scholars will explore different pathways and skills development through research opportunities, internships or co-ops, and post-graduation preparation, all of which develop students’ competencies as STEM practitioners. All of these activities are documented via an e-portfolio that supports students’ construction of their knowledge and identity, while providing a robust tool for program evaluation and knowledge generation. 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.
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会议论文
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