Enhancing Career Outcomes Through Mentoring, Research, and Focused Career Discernment in Science, Technology, Engineering, and Mathematics

该项目将有助于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，支持高成就，低收入学生的保留和毕业，证明经济需要在西雅图大学，一个综合性的私立耶稣会大学约7,500名主要是本科生。在六年的时间里，该项目将为24名攻读生物学、化学或数学学士学位的全日制学生提供奖学金。低收入，学术天赋和第一代学生将获得为期四年的10，000美元奖学金。在机构研究的基础上，从S-STEM计划，研究文献以及对低收入第一代学生独特经历的理解中吸取的经验教训，该项目将提供财政支持以及学术和支持服务系统，以促进学生的成功。通过评估，该项目将评估数据科学早期研究经验作为生物学，化学和数学专业进一步研究和就业的催化剂的重要性。对一项旨在激励使用校园服务和参与项目活动的创新徽章计划的审查，将产生有关游戏化在鼓励参与多维度、结构化职业识别过程中的有效性的知识，从而补充关注课堂环境中游戏化的新兴文献。毕业的学者将拥有数据科学的基本技能，这是国家需求的关键领域，也是一系列STEM行业的宝贵技能。他们将为技术、生命科学/生物技术和环境部门的区域机会做好充分准备。除了直接服务的学生，该计划将改善西雅图大学的机制，连接所有STEM专业，以支持整个校园的办公室，增加我们多样化的学生群体的保留和职业准备。该项目的总体目标是提高低收入，高成就的本科生与证明财政需要完成STEM学位。四个关键目标指导该项目。首先是向低收入家庭、在生物学、化学或数学专业有学术天赋的学生提供奖学金。其次是提高低收入家庭学生在这些领域的毕业率。第三是为学生提供数据科学的早期跨学科研究经验和有针对性的职业生涯形成活动。第四，也是最后一点，是提高对如何将学生与学术和职业服务（如辅导和职业规划）联系起来的理解。为了实现这些目标，该项目包括三个主要组成部分：奖励使用支持服务的徽章奖励系统;职业识别工具包，鼓励学生探索可能的职业选择;以及第二年的数据科学课程，旨在作为本科研究的切入点。该项目将采用混合方法设计，评估学生参与项目活动对学业成功和就业成果的影响，以及游戏化在鼓励使用校园服务方面的有效性。通过该计划，如徽章，职业识别工具包和跨学科研究课程，适应或开发有前途的做法，将通过大学网站，会议演示和出版物广泛传播到其他学院和大学。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，并产生有关学术成功，保留，转移，毕业和学术/职业途径的知识。该奖项反映了NSF的法定使命，并被认为值得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来支持。

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 Seattle University, a comprehensive private Jesuit university of approximately 7,500 primarily undergraduate students. Over its six-year duration, this project will fund scholarships to 24 unique full-time students who are pursuing bachelor’s degrees in biology, chemistry, or mathematics. Low-income, academically-talented, and first-generation students will be awarded scholarships of $10,000 for four years. Building on institutional research, lessons learned from prior awards from the S-STEM program, the research literature, and an understanding of the unique experiences of low-income first-generation students, the project will provide financial support and a system of academic and support services to foster student success. Through evaluation, the project will assess the significance of an early research experience in data science as a catalyst for biology, chemistry, and mathematics majors’ further research and job placement. Examinations of an innovative badging program to incentivize the use of campus services and participation in project activities will generate knowledge about the effectiveness of gamification in encouraging participation in a multi- dimensional, structured career discernment process, thus complementing an emergent literature focused on gamification in classroom settings. Graduating scholars will have fundamental skills in data science, a critical area of national need and a valuable skill set across a range of STEM industries. They will be well prepared for regional opportunities in the technology, life sciences/biotech, and environmental sectors. Beyond the students directly served, this program will improve Seattle University’s mechanisms for connecting all STEM majors to support offices across campus, increasing the retention and career preparation of our diverse student body. The overall goal of this project is to increase STEM degree completion of low-income, high-achieving undergraduates with demonstrated financial need. Four key objectives guide the project. First is to award scholarships to low-income, academically talented students majoring in biology, chemistry, or mathematics. Second is to increase graduation rates of low-income students in those fields. Third is to provide students with an early, interdisciplinary research experience in data science and targeted career formation activities. Fourth, and finally, is to improve understanding of how to connect students with academic and career services, such as tutoring and career planning. To meet these objectives, the project includes three major components: a badge-award system to incentivize the use of support services; a Career Discernment Toolkit, which encourages students to explore possible career options; and a second-year data science course, which is designed as an entry point into undergraduate research. Using a mixed methods design, the project will assess the impact of student participation in project activities on academic success and employment outcomes and the effectiveness of gamification in encouraging the use of campus services. Promising practices adapted or developed through this program, such as badging, the Career Discernment Toolkit, and the interdisciplinary research course, will be disseminated broadly to other colleges and universities through the University website, conference presentations, and 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 ofThis 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.