Analyzing the Impact of the Meyerhoff Scholars Program

这项建议旨在加深人们对博士学位途径的了解。 巴尔的摩马里兰大学迈耶霍夫奖学金计划(MSP)参与者 县(UMBC)，并为该计划的索赔建立更坚实的因果基础 冲击力。方案的主要重点是增加代表不足的少数族裔的数量 科学家和工程师，尤其是非裔美国人。MSP带来了一项全面的 为实现这一目标提供一系列支持，包括：一项全面的一揽子财务计划 取决于在科学、技术、工程或数学方面保持B平均分 (STEM)专业；大一前为期6周的夏季桥牌项目；全职顾问 定期监督和支持学生；像家庭一样的社会和学术支持 系统；广泛的教职员工参与(包括作为研究导师)；以及参与 暑期研究实习。我们利用定量和定性的方法来增强 理解为什么一些MSP参与者攻读并完成博士学位，而另一些人则没有 (研究一)，并将MSP参与者的STEM博士结果与对照进行比较 非参与者样本(研究二)。 我们的第一个具体目标是测试一个概念模型，该模型将大学预科学生的特征与 学生在MSP中的经历和在大学的成功，以及由此而来的途径 从大学到攻读博士学位和获得博士学位都有变数。结构方程建模将是主要的 在这方面的研究中采用的是方法，辅以定性的方法。 第二个具体目标是建立更强有力的因果关系推论 迈耶霍夫奖学金计划，使用一种避免许多潜在来源的方法 在过去评估MSP和其他影响的努力中可能存在的偏见 目标相似的干预策略。具体地说，倾向分数匹配将用于 这方面的研究。

This proposal is designed to enhance understanding of the pathways to the PhD among Meyerhoff Scholarship Program (MSP) participants at the University of Maryland, Baltimore County (UMBC), and to develop a more solid causal foundation for claims of the program's impact. The primary program emphasis is to increase the number of underrepresented minority scientists and engineers, especially African American. The MSP brings to bear a comprehensive array of supports toward achievement of this goal, including: a comprehensive financial package contingent upon maintaining a B average in a science, technology, engineering or mathematics (STEM) major; a pre-freshmen year 6-week Summer Bridge Program; full-time advisors who monitor and support students on a regular basis; a family-like social and academic support system; widespread faculty involvement (including as research mentors); and participation in summer research internships. We utilize quantitative and qualitative methods to enhance understanding of why some MSP participants pursue and complete PhDs while others do not (Study One), and to compare the STEM PhD outcomes of MSP participants with a comparison sample of non-participants (Study Two). Our first specific aim is to test a conceptual model linking pre-college student characteristics to student experience in the MSP and success in college, and in turn, the pathways from these college variables to PhD pursuit and receipt. Structural equation modeling will be the primary approach used in this aspect of the research, supplemented by qualitative methods. The second specific aim is to establish stronger causal inferences regarding the efficacy of the Meyerhoff Scholarship Program by using an approach that avoids many of the potential sources of bias that may be present in past efforts to estimate the impact of the MSP and other intervention strategies with similar goals. Specifically, propensity score matching will be used for this aspect of the research.