NSF STEM Scholarship and Mentoring Program

该项目是在之前S-STEM项目的基础上进行的，该项目对提高STEM的招生人数和学生多样性产生了重大影响，并进一步提高了其有效性。具体地说，该项目将在四年内提供25个奖学金，每个奖学金每年5200美元。它正在扩大现有的指导计划，包括促进职业探索的活动，特别是通过自我选择的体验式学习模块，在那里学生追求他们在学术和职业发展方面的兴趣。它通过基于学业进步、职业兴趣和入学时收集的预测性信息的个性化、数据驱动的方法，提高了个性化学生指导的有效性。最后，它正在开发一个在线应用程序，以确定学生对STEM领域的兴趣水平。这有助于挑选对工程和科学感兴趣的学生，并为他们提供建议。该项目特别招募妇女和代表性不足群体的成员。该项目的结果具有智力价值，特别是数据驱动的辅导方法的发展及其预测和提高学生在STEM领域的成功的能力。评估数据包括对全国规范的工程领域妇女评估调查的答复。这使得可以与其他机构进行数据比较，并促进方案结果的传播。更广泛的影响包括STEM毕业生的持续增长，包括该大学代表不足的群体。他们构成了宾夕法尼亚州西北部及更远地区的技术人才库。开发的模式、指导计划和以数据为导向的学生咨询方法可以移植和适应其他机构。

This project is building upon a prior S-STEM project that had a significant impact on improving STEM enrollments and student diversity, and further improving its effectiveness. Specifically, the project is offering 25 scholarships of $5,200 each per year over a four year period. It is expanding the existing mentoring program, including activities that facilitate career exploration, particularly through a self-selected Experiential Learning Module, where students pursue their interests in academic and career development. It is enhancing the effectiveness of individualized student mentoring through a personalized, data-driven approach based on academic progress, career interests, and predictive information collected at the time of matriculation. Finally, it is developing an online application that determines students' level of interest in STEM fields. This helps select and advise students interested in engineering and science. The project especially recruits women and members of underrepresented groups. The results of this project have intellectual merit, particularly the development of the data-driven approach to mentoring and its ability to predict and improve student success in STEM fields. The assessment data include responses to nationally-normed Assessing Women in Engineering surveys. That allows comparison of data with other institutions and facilitates dissemination of program results. The broader impacts include continued growth of STEM graduates, including underrepresented groups, at the university. They constitute a pool of technical talent for the northwestern Pennsylvania region and beyond. The model developed, the mentoring program, and the data-driven approach to student advising are transferable and adaptable to other institutions.