Enhancing Career and Academic Pathways through High-Quality Evidence-Based Educational Practices

该项目将通过利用由加州和德克萨斯州四所高等教育机构组成的联盟，满足全国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。在为期6年的时间里，该项目将向表现出经济需求的成绩优异的低收入学生提供85份奖学金，其中24名学生将在一所附属大学获得计算机科学（CS）副学士学位，然后转入一所合作的四年制大学，获得计算机科学学士学位。学者将获得最多四年的资助，并有可能额外一年完成研究生学位。学者们将积极参与网络安全、数据科学和专业发展方面的课外活动，以支持他们在本科和研究生阶段的学习。该计划的目标是帮助学者找到满足行业需求的全职工作机会。即将毕业的学者将为21世纪网络安全和数据科学的行业需求和重大挑战做出贡献。该项目的研究部分将向教育研究和计算社区提供有关创建包容性计算学习环境所需的具体要素的信息，同时还将建立有关促进基于证据的改革的采用和可持续性的因素的知识基础，这些改革为低收入，有学术天赋的计算学生提供服务。本研究将利用社会文化的视角来考察S-STEM学者如何发展和扩大计算实践社区。研究方法将包括参与者观察，半结构化的个人和小组访谈，文献分析和调查方法。分析将包括归纳和演绎编码实践，持续的比较分析，以及学生成绩差异的统计分析。该项目由美国国家科学基金会的科学、技术、工程和数学奖学金项目资助，旨在增加有经济需求的低收入学术天才学生在STEM领域获得学位的人数。它还旨在改善未来STEM工作者的教育，并为低收入学生提供有关学业成功、留校、转学、毕业和学术/职业道路的知识。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识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 leveraging an established consortium of four institutions of higher education across California and Texas. Over its 6-year duration, the project will provide 85 scholarships to high-achieving, low-income students with demonstrated financial need, of which 24 will earn an associate degree in Computer Science (CS) at a feeder college, then transfer to a partnering consortium 4-year institution to earn a bachelor’s degree in CS. Scholars will be funded for up to four years, with the possibility for an additional year to complete a graduate degree. Scholars will actively engage in co-curricular activities focused on cybersecurity, data science, and professional development to support their trajectories through undergraduate and graduate studies. The goal of the program is to help position scholars for full-time career opportunities that meet the needs of the industry. Graduating scholars will be equipped to contribute to industry demands and grand challenges of the 21st century in cybersecurity and data science.The research component of this project will inform the education research and computing communities about the specific elements that are needed to create inclusive learning environments in computing, while also building a foundation of knowledge on factors that facilitate the adoption and sustainability of evidence-based reforms that serve low income, academically talented students in computing. This study will utilize a sociocultural lens to examine how S-STEM scholars develop and expand communities of computing practice. Research methods will include participant observation, semi structured individual and group interviews, document analysis, and survey methods. Analysis will involve inductive and deductive coding practices, constant comparative analysis, and statistical analysis of differences in student outcomes. 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.