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1. “If I knew what else I should do, I would have left by now:” Two engineering PhD students’ experiences with Master’s-level departure

   Zerbe, E.; Berdanier, C.G.P. (October 2019, IEEE Frontiers in Education Conference)

   This Research Full Paper presents two examples of doctoral engineering attrition. To date, little research has been conducted on the many compounding factors that lead to attrition in graduate programs. In this paper, we present the narratives of two doctoral PhD students, Kelsey and Amy, who were deciding on departing from the engineering PhD. These narratives embody a deeper investigation of academic self-concept development through graduate school, with a focus on the decision-making processes to continue in the PhD program or decide to depart with a Master’s degree. At the time of the interviews, both participants were still enrolled in their programs, but one had definite plans to depart and left shortly after the interview. This study is one of the first that highlights the role of the Master's degree as an off-ramp from the engineering doctorate and lends insight to narratives surrounding attrition in engineering: Despite academic success in their courses and successful research progress, these participants decided to depart even after passing significant milestones such as qualifying exams. This research presents the beginning of a larger research project with a goal of generating a more complete narrative of the attrition process for the students, with an explicit focus on Master's-level departure. 

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2. Characterizing Doctoral Engineering Student Socialization: Narratives of Mental Health, Decisions to Persist, and Consideration of Career Trajectories

   https://doi.org/10.1109/FIE43999.2019.9028438  

   Hocker, E.; Zerbe, E.; Berdanier, C.G.P. (October 2019, IEEE Frontiers in Education)

   This research full paper explores interview data with N=36 engineering graduate students to understand the factors and characteristics of graduate socialization, with the effort of better preparing students to succeed in doctoral programs. This research is motivated by the alarming fact that nearly one-third of engineering doctoral students will not finish their PhD programs; however, little research has been conducted on the various factors that can lead to attrition or enhance persistence in graduate engineering programs. This paper presents the results from the interview phase of a larger study investigating doctoral engineering socialization, attrition, persistence, and career trajectories. The participants for this study come from large research-intensive universities across the United States, and were sampled for maximum variation in a number of different categories, including stage in their doctoral program, gender, and race. Upon collecting and analyzing interview data from our participants through constant comparative and content analysis methods, several themes arose including concerns for mental health in engineering graduate students and uncertainties with joining the culture of academia in their future careers. Further, although the participants for this study are currently graduate students who anticipate completing their PhDs, nearly half of the participants discussed strongly considered leaving at some point. This study adds to the body of literature surrounding engineering attrition and the underlying issues driving engineering PhDs away from academic engineering careers. 

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3. Mitigating Ceiling Effects in a Longitudinal Study of Doctoral Engineering Student Stress and Persistence

   https://doi.org/10.28945/5118  

   Bahnson, Matthew; Sallai, Gabriella; Jwa, Kyeonghun; Berdanier, Catherine (January 2023, IJEE International Journal of Engineering Education)

   Aim/Purpose: The research reported here aims to demonstrate a method by which novel applications of qualitative data in quantitative research can resolve ceiling effect tensions for educational and psychological research.Background: Self-report surveys and scales are essential to graduate education and social science research. Ceiling effects reflect the clustering of responses at the highest response categories resulting in non-linearity, a lack of variability which inhibits and distorts statistical analyses. Ceiling effects in stress reported by students can negatively impact the accuracy and utility of the resulting data.Methodology: A longitudinal sample example from graduate engineering students’ stress, open-ended critical events, and their early departure from doctoral study considerations demonstrate the utility and improved accuracy of adjusted stress measures to include open-ended critical event responses. Descriptive statistics are used to describe the ceiling effects in stress data and adjusted stress data. The longitudinal stress ratings were used to predict departure considerations in multilevel modeling ANCOVA analyses and demonstrate improved model predictiveness.Contribution: Combining qualitative data from open-ended responses with quantitative survey responses provides an opportunity to reduce ceiling effects and improve model performance in predicting graduate student persistence. Here, we present a method for adjusting stress scale responses by incorporating coded critical events based on the Taxonomy of Life Events, the application of this method in the analysis of stress responses in a longitudinal data set, and potential applications.Findings: The resulting process more effectively represents the doctoral student experience within statistical analyses. Stress and major life events significantly impact engineering doctoral students’ departure considerations.Recommendations for Practitioners: Graduate educators should be aware of students’ life events and assist students in managing graduate school expectations while maintaining progress toward their degree. Recommendation for Researchers: Integrating coded open-ended qualitative data into statistical models can increase the accuracy and representation of the lived student experience. The new approach improves the accuracy and presentation of students’ lived experiences by incorporating qualitative data into longitudinal analyses. The improvement assists researchers in correcting data with ceiling effects for use in longitudinal analyses.Impact on Society: The method described here provides a framework to systematically include open-ended qualitative data in which ceiling effects are present.Future Research: Future research should validate the coding process in similar samples and in samples of doctoral students in different fields and master’s students. 

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4. EmPOWERing a Sustainable Energy Future through Interconnected Curricular and Co-Curricular Pedagogies

   Bielicki, Jeffrey M; Weng, Yun-Han; Creamer, Emily T; Mayhew, Matthew J (May 2024, Proceedings of the 2024 Annual American Society of Engineering Education Research and Exposition Conference)

   In 2019, a National Research Traineeship (NRT) grant from the U.S. National Science Foundation seeded the establishment of a new model for graduate education at Ohio State University – a large, public, land-grant R-1 university in the U.S. Midwest. This grant application involved faculty from eight different colleges within this university (education; engineering; public affairs; arts and sciences; food, agriculture, and environmental sciences; business; law). The Ohio State EmPOWERment Program in convergent graduate training for a sustainable energy future enrolls Ph.D. students studying any aspect of energy from degree programs any college in Ohio State and engages them in several curricular and co-curricular elements that are designed to dovetail with their Ph.D. degree program requirements in ways that do not extend their time to graduate. The Ohio State EmPOWERment Program established at Ohio State an energy Student Community of Practice and Engagement (SCOPE), a Graduate Interdisciplinary Specialization (GIS), and an undergraduate Research in Sustainable Energy (RISE) summer research experience. Over time a JOULE energy seminar series (JOULE) was added to elevate intellectual engagement in for trainees in The Ohio State EmPOWERment Program and broaden their engagement with researchers across this university. This paper investigates the development and accentuation of innovation capacities of Ph.D. trainees in The Ohio State EmPOWERment Program relative to other Ph.D. students who enrolled in science, technology, engineering, and math (STEM) disciplines at Ohio State and did not participate in the Ohio State EmPOWERment Program. This work considers three different constructs for each of three scales (i.e., Interpersonal, Intrapersonal, Cognitive). Of the nine different constructs, six pass assumption tests and pre-test scores for innovation self-concept, proactivity, social networking, risk-taking or tolerance, creative capacity, and intention to innovate are significant predictors of post-test capacities. Overall, participating in The Ohio State EmPOWERment Program appears to be beneficial and may increase innovation self-concept, proactivity, creative, and intention to innovate capacities. 

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5. Capturing First- and Second-Year Master’s Engineering Students’ Perceptions of Support in Their Transitions to Graduate School

   https://doi.org/10.18260/1-2--48443  

   Berdanier, Catherine; Urbina, Julio; Hamilton, Reginald; Cohan, Catherine; Peeples, Tonya; Reed, Cynthia (June 2024, ASEE Conferences)

   The purpose of this research full paper is to investigate issues facing very early-stage master’s students as they transition into a degree program at a large research-intensive university. While there is an increasing focus on graduate and doctoral engineering education, few studies have sought to focus specifically on master’s students, treating them from a research perspective as miniature doctoral students, though it is documented that MS students in engineering have different goals and motivations for pursuing graduate study than PhD students, as well as different anticipated career trajectories. To further compound these gaps in the literature, most studies assume that doctoral students in engineering come from historically privileged socioeconomic backgrounds. National conversations are clear that to broaden participation in engineering, the educational community must attend to the specific needs of students from low-income backgrounds. These students may also not have access to the social and cultural capital required to navigate graduate school, since many are first-generation graduate students and because systems of education are traditionally designed for students from upper class backgrounds. To this end, this study explores the experiences of first-semester graduate students supported in part by funding aimed to support master’s students and have demonstrated unmet financial need. Interviews were conducted with six first- and second year master’s students and analyzed using thematic analysis methods employing Posselt’s Framework for Doctoral Student Support—here, extended to master’s students—to elicit information about surprises, expectations, and unanticipated issues facing this special population of students. Findings indicate that there are several easily implemented structural modifications programs and faculty can take that can facilitate the transition to graduate school for graduate students, low-income and otherwise. 

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