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This empirical research full paper describes a project aimed at increasing graduation rates among low-income, academically talented engineering students by implementing first-year student initiatives. The project, supported by an NSF-SSTEM (National Science Foundation Scholarships in Science, Technology, Engineering and Mathematics) grant at a Northeastern US institution, is in its second year of a four-year plan. Grounded in Tinto’s conceptual model of student motivation and persistence, the project emphasizes early interventions, which are critical for low-income students facing external challenges that may impact their decision to stay in college or enter the workforce. We developed and integrated the SSTEM project aiming to increase four key elements, which based on Tinto will also increase persistence. The SSTEM project includes scholarships, an Engineering Learning Community (ELC) that promotes cohort-based learning and living, mentorship, and participation in personal and professional development seminars. Additionally, inclusive practices have been integrated into first-year engineering lab courses to improve curriculum accessibility. This paper evaluates the validity of an instrument designed to assess the project's impact on students’ college experiences and persistence. It builds on prior exploratory factor analysis (EFA) research by presenting confirmatory factor analysis (CFA) findings to further validate the instrument. 

Increases in the representation of Black and Latiné students in doctoral engineering programs over the past decades have not yet led to long-term success in achieving parity with the population's demographics. Although graduation rates show such students are recruited to such programs, they remain underrepresented due to their early departure due to unreconcilable differences in institutional cultures being exclusive of their identities. Although the socialization experiences of first-year doctoral students can predetermine their success or failure, scant research has looked at Black and Latiné students in engineering programs. This longitudinal qualitative case study explores the first-year program experiences of such students and how their minority identities influenced theirsocialization. We present the experiences of sixteen engineering graduate students from variousinstitutions who met in virtual focus groups throughout their first year. We found that Black and Latiné students' racial-ethnic identities influence how they experience the first year of their doctorate.This influence extends from how they perceive their sense of belonging and qualification to be in such programs to how and where they seek support when facing racialized experiences. Moreover, participants shared how their programs were not equipped to support their identities and potential contributions to their fields. These findings are key to the engineering context, where representation is starkly limited for these students. Our implications for institutions focus on the needed cultural shifts to ultimately diminish the barriers that Black and Latiné students face while pursuing doctoraldegrees. 

Several studies have shown that underrepresented minorities (URM) (African Americans, Native Americans, Pacific Islanders, and Latinos) are more likely to drop out of engineering doctorate programs before graduation compared to international and majority students. In addition, transitioning into the doctoral programs without having a good understanding of what it entails can make the PhD experience difficult. To address this issue, a team of researchers from four US universities developed a project called “the Rising Doctoral Institute (RDI)’’. One of the research goals of this project is to better understand how factors in the academic system interact dynamically to influence (i.e., support or hinder) incoming URM students’ access, success, persistence, and retention in engineering doctoral programs. To accomplish this goal, we will use a comprehensive analysis approach known as System Dynamic Model (SDM). This work-In-Progress article represents the starting point to develop this model and its overall goal is to conduct a systematic literature review to identify the factors in the academic system that impact URM students’ experience in doctoral engineering programs. We followed a process suggested by Okoli and Schabram [1] which consists of four major steps. The first step is presenting the purpose of the literature review, protocol, and training. The second step consists of selecting the literature and practical screen. The next step is the quality appraisal and data extraction. Finally, the analysis of findings and writing the review. By identifying the factors and the relation between them, we could help ensure a more diverse and equitable STEM education. Although some external factors can affect students’ access, success, persistence and retention in engineering PhD programs, this study is limited to exploring the factors and interactions within the academic system that can potentially impact the successful experience of underrepresented minorities in PhD programs in engineering such as Advisor-Advisee Relationship, Student’s Experience, Academic Support and Faculty-Students Interaction