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1. The Rising Doctoral Institute: Preparing Minority Students for the Transition into the Engineering Ph.D.

   Artiles, M.S ; Cruz-Bohorquez, J ; Matusovich, H.M ; Adams, S.G ; Lee-Thomas, G. ( January 2021 , ASEE Annual Conference proceedings)

   Studies on graduate education have shown that underrepresented minorities finish PhDs in engineering at lesser rates and longer timeframes than their majority counterparts. While multiple interventions have been designed for students considering their decision to apply for graduate school or students completing their doctoral journey, few focus on the transition into those doctoral programs. To prepare minoritized doctoral students for this transition to the Ph.D., we developed and researched the Rising Doctoral Institute (RDI). The RDI is a four-day summer workshop for incoming doctoral students who identify as underrepresented in engineering and intend to begin graduate school in the Fall semester. This paper aims to discuss the process through which we developed the RDI and our initial research findings. We conclude with our plan to disseminate these workshops across multiple US institutions using a change-theory informed dissemination model 

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2. The Rising Doctoral Institute: Preparing Minority Students for the Transitioninto the Engineering Ph.D. Proceedings

   Artiles, M.S. ; Cruz-Bohorquez, J. ; Matusovich, H.M. ; Adams, S.G. ; & Lee-Thomas, G. ( January 2021 , ASEE Annual Conferences and Exposition)

   Studies on graduate education have shown that underrepresented minorities finish PhDs in engineering at lesser rates and longer timeframes than their majority counterparts. While multiple interventions have been designed for students considering their decision to apply for graduate school or students completing their doctoral journey, few focus on the transition into those doctoral programs. To prepare minoritized doctoral students for this transition to the Ph.D., we developed and researched the Rising Doctoral Institute (RDI). The RDI is a four-day summer workshop for incoming doctoral students who identify as underrepresented in engineering and intend to begin graduate school in the Fall semester. This paper aims to discuss the process through which we developed the RDI and our initial research findings. We conclude with our plan to disseminate these workshops across multiple US institutions using a change-theory informed dissemination model. 

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3. The Quest for URM Doctoral Persistence: An Analysis of Feedback Loops in the Academic System

   Cano, M ; Corey-Weinberg, M. ; Rodriguez Mejia, E. ; Cruz, J.M. ; Lee-Thomas, G. ; Matusovich, H.M. ; Artiles, M.S. ; & Adams, S.G. ( June 2023 , ASEE Annual Conference proceedings)

   Studies have shown that the graduation rate for underrepresented minorities (URM) students enrolled in engineering doctorates is significantly lower than their peers. In response, we created the “Rising Doctoral Institute (RDI)”. This project aims to address issues that URM students encounter when transitioning into a Ph.D. in engineering and their decision to persist in the program. To suggest institutional policies that increase the likelihood of URM students to persist in their doctorate, we identify and analyze some factors in the academic system that reinforce or hinder the retention of URM students in doctoral education. Although the factors that influence persistence in URM students have been largely studied as direct causes of attrition or retention, there is a need for a system perspective that takes into account the complexity and dynamic interaction that exists between those factors. The academic system is a complex system that, by nature, is policy resistant. This means that a positive variation of a factor can incur unintended consequences that could lead to a negative variation in other factors and ultimately hinder the positive outcomes of that policy. In this work-in-progress article, we analyze the dynamics of the factors in the academic system that reinforce or hinder the retention of URM graduate students in engineering. The purpose is to build some of the causal loops that involve those factors, to improve the understanding of how the complex system works, and prevent unintended consequences of institutional policies. We used Causal Loop Diagrams (CLD) to model the feedback loops of the system based on initial hypotheses of causal relationships between the factors. We followed a process that started with establishing hypotheses from a previous literature review, then using a different set of articles we identified the factors related to the hypotheses and the causal links between them. Next, we did axial coding to group the concepts into smaller categories and established the causal relations between categories. With these categories and relations, we created the CLDs for each hypothesis. For the CLDs that have connections missing to close the loop, we went to find additional literature to close them. Finally, we analyzed the implications of each CLD. In this article, we analyze and describe three major CLDs found in literature. The first one was built around the factor of having a positive relationship with the supervisor. The second centered on the student’s experience. The third focused on factors that relate to university initiatives 

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4. System Factors Affecting Underrepresented Minorities in Doctoral Programs in Engineering: A Literature Review

   https://doi.org/10.1109/FIE49875.2021.9637208  

   Bouhrira, Neirouz ; Cruz, Juan M. ( October 2021 , 2021 IEEE Frontiers in Education Conference (FIE))

   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 

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5. A latent class analysis approach to the identification of doctoral students at risk of attrition

   https://doi.org/10.1371/journal.pone.0280325  

   Stevens, Samantha M. ; Ruberton, Peter M. ; Smyth, Joshua M. ; Cohen, Geoffrey L. ; Purdie Greenaway, Valerie ; Cook, Jonathan E. ( January 2023 , PLOS ONE)

   Benetreau, Yann (Ed.)

   To advance understanding of doctoral student experiences and the high attrition rates among Science, Technology, Engineering, and Mathematics (STEM) doctoral students, we developed and examined the psychological profiles of different types of doctoral students. We used latent class analysis on self-reported psychological data relevant to psychological threat from 1,081 incoming doctoral students across three universities and found that the best-fitting model delineated four threat classes: Lowest Threat , Nonchalant , Engaged/Worried , and Highest Threat . These classes were associated with characteristics measured at the beginning of students’ first semester of graduate school that may influence attrition risk, including differences in academic preparation (e.g., amount of research experience), self-evaluations and perceived fit (e.g., sense of belonging), attitudes towards graduate school and academia (e.g., strength of motivation), and interpersonal relations (e.g., perceived social support). Lowest Threat students tended to report the most positive characteristics and Highest Threat students the most negative characteristics, whereas the results for Nonchalant and Engaged/Worried students were more mixed. Ultimately, we suggest that Engaged/Worried and Highest Threat students are at relatively high risk of attrition. Moreover, the demographic distributions of profiles differed, with members of groups more likely to face social identity threat (e.g., women) being overrepresented in a higher threat profile (i.e., Engaged/Worried students) and underrepresented in lower threat profiles (i.e., Lowest Threat and Nonchalant students). We conclude that doctoral students meaningfully vary in their psychological threat at the beginning of graduate study and suggest that these differences may portend divergent outcomes. 

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