Using Evidence-Based Educational Practices to Prepare and Support Highly Qualified Students with Financial Need for Careers in Computing and Cyber-Security

该项目将通过德克萨斯州和加利福尼亚州的两所四年制大学以及两所合作的两年制大学（德克萨斯大学埃尔帕索分校（UTEP）、加州州立大学斯坦尼斯劳斯分校（CSU-S）、埃尔帕索社区学院（EPCC）和默塞德学院（MC））组成的财团建立一个奖学金计划。该项目将为低收入、有学术天赋的学生进入计算机科学和网络安全等高需求领域的劳动力市场做好准备。S-STEM学者将参加课外活动，积极参与专业发展活动，支持他们的本科学习轨迹，特别是从两年制大学到四年制大学，并获得高级学位。该项目将建立在西班牙裔服务机构（CAHSI）计算联盟的有效实践和战略，由NSF （CNS-1042341）资助。作为CAHSI的领导机构，UTEP将根据CAHSI支持学生成功的成熟实践，协调该项目活动的实施。这些活动包括：关注学生专业、沟通和研究/工作技能发展的亲和研究模式；提供资源、信息和指导的指导；CAHSI峰会为学生提供了与行业代表建立联系、参加技术研讨会、为面试和实习做准备的机会。该项目将有一个专门的网站，由每个参与的四年制大学托管，并将利用社交媒体联系潜在的申请人。此外，每所四年制大学将开展面对面的招聘活动，包括每年为期两天的活动，为来自地区高中、大学和合作的两年制大学的潜在申请者提供服务。该活动将包括高度互动的活动，以建立对计算机学位的兴趣，并讨论职业道路，包括在工业、政府、非政府组织的工作和创业机会。这些活动还将强调高等教育的重要性。该项目将调查针对目标学生群体的综合循证实践的有效性，并将通过对导致目标计算机学生群体的招聘、保留和获得学位的因素的新理解，为现有知识库做出贡献。特别是，它将确定学生在多大程度上将网络安全作为一个专业领域，以及哪些活动对学生特别有吸引力。该研究将利用社会文化、情境学习的视角来研究S-STEM学者如何发展和扩大计算实践社区。研究方法包括：参与观察、半结构化的个人和小组访谈、文献分析（包括机构研究数据分析）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，以及学生结果差异的统计分析（例如，转学率，GPA，研究生入学意向）。这项研究将向教育研究和计算机科学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，同时还将建立一个急需的知识基础，以促进基于证据的改革的采用和可持续性，为低收入、高素质的计算机学生提供服务。

This project will establish a scholarship program through a consortium of two four-year institutions in Texas and California and two partner two-year colleges: the University of Texas at El Paso (UTEP), California State University-Stanislaus (CSU-S), El Paso Community College (EPCC), and Merced College (MC). The project will prepare low-income, academically talented students to enter the workforce in the high demand areas of computer science and cyber-security. S-STEM scholars will participate in co-curricular activities that actively engage them in professional development activities that support their trajectories through undergraduate studies, in particular from two-year colleges to four-year institutions, and onto advanced degrees. The project will build on the effective practices and strategies of the Computing Alliance of Hispanic-Serving Institutions (CAHSI), funded by NSF (CNS-1042341). As the lead institution of CAHSI, UTEP will coordinate the implementation in this project of activities based on CAHSI's proven practices that support student success. Such activities include: the Affinity Research model that focuses on student professional, communication, and research/workplace skills development; mentoring that provides access to resources, information, and guidance; and the CAHSI Summit that provides opportunities for students to network with industry representatives, participate in technical workshops, and prepare for interviews and internships. The project will have a dedicated website hosted by each participating four-year institution, and it will use social media to reach potential applicants. In addition, each four year institution will employ face-to-face recruitment activities that include an annual two-day event for a pool of potential applicants from area high schools, the university, and partnering two-year colleges. The event will include highly interactive activities to build interest in computing degrees and discuss career pathways, including jobs in industry, government, non-governmental organizations, and entrepreneurial opportunities. The activities will also stress the importance of advanced education.The project will investigate the effectiveness of integrated evidence-based practices with the targeted student population and will contribute to the existing knowledge base with new understandings regarding factors that lead to the recruitment, retention, and degree attainment of the target population of students in computing. In particular, it will identify to what extent students pursue cyber-security as an area of expertise and which activities are particularly compelling for students. The research will utilize a sociocultural, situated learning lens to examine how S-STEM scholars develop and expand communities of computing practice. Research methods include the following: participant observation, semi-structured individual and group interviews, document analysis (including institutional research data analysis), and survey methods. Analysis will involve inductive and deductive coding practices, constant comparative analysis, and statistical analysis of differences in student outcomes (e.g., transfer rate, GPA, intentions for graduate school). The research study will inform the education research and CS communities about the specific elements that are needed to create inclusive learning environments in computing, while also building a much-needed foundation of knowledge on factors that facilitate the adoption and sustainability of evidence-based reforms that serve low income, highly qualified students in computing.