Boosting Access to Data Science Scholars

增加接触数据科学学者的机会

• 批准号: 2130070
• 负责人: Michelle Trim
• 金额: $ 150万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2027-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2130070&HistoricalAwards=false
• 关键词: Boosting; Access; Data; Science; Scholars

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 Massachusetts Amherst. Over its 6-year duration, this project will provide scholarships to 40 unique full-time students who are pursuing bachelor’s degrees in Informatics or Computer Science in the College of Information and Computer Sciences (CICS). First-year students will receive four years of scholarship support and transfer students will receive two-year scholarships. This project aims to increase student persistence in STEM fields by linking scholarships with evidence-based supports, including faculty and near-peer mentoring, faculty led advising, mentored research experiences, graduate school and career preparation, and participation in discipline-specific conferences. Scholars will work with faculty and near-peer mentors to develop individual academic plans outlining their areas of interest and steps toward achieving their goals. The project will also support curriculum improvements aimed at increasing first-year student retention and decreasing time to completion in STEM. The data science focus of the informatics major at UMass Amherst and the diverse population of students served by the institution will contribute to broadening participation in a critical workforce area. The project also has the potential to increase understanding about the impact that an applied educational emphasis within computing can have on the recruitment, retention, and time to completion for this student population. The overall goal of this project is to increase STEM degree completion of low-income, high-achieving undergraduates with demonstrated financial need. There are three specific aims: expand access to high quality data science career and research pathways; improve the retention rate of first-year students; and decrease time to completion for community college transfer students. External pressures such as financial stress coupled with psycho-social factors such as imposter phenomenon, stereotype threat, and lack of role models have all been documented to impact student success in STEM. Less is known about the impact of an applied educational focus coupled with discipline-specific student success supports on the retention and persistence of students who are first-generation and from populations underrepresented in STEM. Through interviews and other qualitative methods, the ongoing evaluation of the project will advance understanding of the student scholars’ perceived efficacy of the discipline specific support services and the significance of pursuing an applied educational focus. These results will be compared to existing reports such as the NSSE (National Study of Student Engagement) and to the results of the annual UMass Amherst Senior Survey. Additionally, evaluating student success efforts across the parallel cohorts of community college transfer and 4-year students will enable project leaders to recognize and report areas where the met and unmet needs of the two populations diverge. Lessons learned will be disseminated to the broader STEM and computer science education community. 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.

该项目将支持马萨诸塞大学阿默斯特分校有经济需要的成绩优异、低收入学生的保留和毕业，从而满足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。该项目为期 6 年，将为 40 名在信息与计算机科学学院 (CICS) 攻读信息学或计算机科学学士学位的独特全日制学生提供奖学金。一年级学生将获得四年的奖学金支持，转学生将获得两年的奖学金。该项目旨在通过将奖学金与基于证据的支持联系起来，提高学生在 STEM 领域的坚持，包括教师和同行指导、教师主导的建议、指导研究经验、研究生院和职业准备以及参加特定学科会议。学者们将与教师和近同龄导师合作，制定个人学术计划，概述他们感兴趣的领域以及实现目标的步骤。该项目还将支持课程改进，旨在提高一年级学生的保留率并缩短 STEM 课程的完成时间。麻省大学阿默斯特分校信息学专业的数据科学重点以及该机构服务的多元化学生群体将有助于扩大关键劳动力领域的参与。该项目还有可能加深人们对计算领域应用教育重点对学生群体的招收、保留和完成时间的影响的了解。该项目的总体目标是提高有经济需求的低收入、成绩优异的本科生完成 STEM 学位的机会。有三个具体目标：扩大获得高质量数据科学职业和研究途径的机会；提高一年级学生的保留率；并缩短社区大学转学生的完成时间。据记录，经济压力等外部压力以及冒名顶替现象、刻板印象威胁和缺乏榜样等社会心理因素都会影响学生在 STEM 方面的成功。人们对应用教育重点以及特定学科学生成功支持对第一代学生和 STEM 中代表性不足人群的学生保留和坚持的影响知之甚少。通过访谈和其他定性方法，对该项目的持续评估将加深对学生学者对学科特定支持服务的感知效果以及追求应用教育重点的重要性的理解。这些结果将与 NSSE（全国学生参与度研究）等现有报告以及麻省大学阿默斯特分校年度高级调查的结果进行比较。此外，评估社区大学转学学生和四年制学生平行群体的学生成功努力将使项目负责人能够识别并报告两个群体的已满足和未满足需求的差异领域。汲取的经验教训将传播给更广泛的 STEM 和计算机科学教育界。该项目由 NSF 科学、技术、工程和数学奖学金项目资助，该项目旨在增加具有经济需求的低收入学术天才学生获得 STEM 领域学位的数量。它还旨在改善未来 STEM 工作者的教育，并产生有关低收入学生的学业成功、保留、转学、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。